Multi-component picture or video coding concept

Abstract

To provide a multi-component picture or video coding concept that enables higher coding efficiency.SOLUTION: In an encoder 100, the coding efficiency of a multi-component picture or video coding concept is improved by reconstructing a third component signal 30 relating to a third component of the multi-component video using inter-component prediction from a reconstructed first component signal 22 and a reconstructed second component signal 26.SELECTED DRAWING: Figure 3

Description

[Technical Field]

[0001] The present invention is applicable to multi-component image coding, e.g., color image or video coding. Or video coding.

[0002] Colored images and videos are expressed in three or four dimensions, so-called color spaces. The three components are also called components. An example of a color space is the R'G'B' color space. In this color space, the primary colors red (R'), green ( Blue (G'), and blue (B') form the basis of a three-dimensional color cube. However, signal processing applications In the application space, image and video compression is often driven by power consumption, implementation cost, or compression. Minimizing the correlation between different components to achieve high efficiency in terms of efficiency is Therefore, the R'G'B' signals are divided into two components: the first component called luminance (Y ') and the remaining two components called chroma elements (C b C r ) in Y'C b C r for a while In contrast to the R'G'B' color space, the Y'C b C r The value of the saturation component of or red. Therefore, chroma energy is often However, certain transformations, i.e., Y'C b C r Due to the application of R'G'B' conversion to The possibility of overcoming such limitations is limited by the color components. Such predictions are often applied to local predictions between components. It is called Interchange Color Prediction (ICP). ICP is a combination of R'G'B' and Y'C b C r Apply to both signals In the first case, the ICP reduces the energy due to the chroma element. and therefore it can be treated as an alternative to external color space conversion. In the second case, the ICP approach provides further decorrelation steps between the different color components. The ICP approach is therefore more This results in high compression efficiency. For simplicity, we use the residuals regardless of the native or input color space. The following description shows the first and main components and the first or second chroma elements. For, respectively, C b or C r to indicate the two remaining chroma components. or Y'. Processing instructions may occur sequentially for some applications. It is important to note that the order of the chroma components can be important. be. Summary of the Invention [Problem to be solved by the invention]

[0003] However, for example, it is not possible to predict one chroma element based on the other chroma elements. By doing the same for the 'ma' element, ICP is applied in pairs, even if it does However, it would be advantageous to be able to further increase coding efficiency.

[0004] The object of the present invention is to provide a method for coding multi-component images or videos that allows for higher coding efficiency. The objective of this paper is to provide a concept for video encoding.

[0005] This object is achieved by the subject matter of the independent claims of the present application. [Means for solving the problem]

[0006] The concept of multi-component image coding efficiency or video coding has been restructured. The component is extracted from the first component signal and the reconstructed second component signal. Inter-component prediction is used to obtain a third-order prediction for the third component of a multi-component video. The fact that the present invention may be improved by reconstructing the component signals of This is a fundamental discovery.

[0007] According to an embodiment of the present invention, different or multiple ICP encoding modes can be used. Within the ICP mode portion of a component image or video data stream, The transmission of multiple source ICP signals is used to switch between ICP encoding modes. , including a plurality of source ICP coding modes and at least one non-ICP coding mode. ICP mode part of multi-component image or multiple source ICP coding mode In a video where For this purpose, the same may be used to denote spatially corresponding portions of the reconstructed first component signal or Prediction from the spatially corresponding parts of the constructed second component signal or a combination of both The signaling indicates whether there is inter-component prediction for each subpart. In at least one non-ICP coding mode, and spatially corresponding portions of the reconstructed first component signal and the reconstructed second component signal. This kind of combination or alteration between spatially corresponding portions of two component signals is Not available. ICP is fully supported in ICP mode parts of non-ICP coding modes. The ICP may be switched off, or the ICP may simply The ICP mode section may be used for a single image. , a single image sequence or a single slice or consecutively coded images, an image sequence It may be in cans or slices. Involved in parameterizing sub-picture granularity for multi-source ICP according to embodiments of the present invention At least one non-ICP coding mode that can be used, and transmission options for any additional signals. Overhead and coding modes Multiple source ICP juxtaposition and non-ICP coding In the case of multiple source ICPs, the coding is performed in relation to the encoding mode. It can be restricted to at least one non-ICP encoding mode and multiple source ICP encoding modes. By juxtaposing the signaling modes, any additional signaling overhead is now Involved in parameterizing sub-picture granularity for multi-source ICP according to embodiments of the invention and it can be used to encode multiple source ICP codes associated with non-ICP coding modes. This additional signaling overhead can be increased in the case of a multi-mode Codes obtained from multiple component sources can be used for inter-component prediction. The coding efficiency improvement may be limited to the portion of the video that is overcompensated.

[0008] According to an embodiment, the first component is luminance and the second component is the first The third component is the second chroma component. In this case, the combined composition of the second chroma component and the further first chroma component based on the luminance component is Inter-component prediction is coded using, for example, transform and entropy coding. Improve the decorrelation of the residuals.

[0009] According to an embodiment, explicit ICP source signaling in the data stream is reconstructed. using inter-component prediction from the spatially corresponding parts of the first component signal. The third component signal in the current image of a multi-component image or video and reconstructing the spatially corresponding second component signal. Multi-component image or video using inter-component prediction from the corresponding parts During reconstruction of the third component signal in the current picture, sub-picture granularity Despite the overhead of sending signals, this method The available prediction improvements therefore overcompensate for the signal transmission overhead. This leads to higher coding efficiency. Alternatively, implicit signaling can be used. Regardless of the type of signal transmission used, the sub-picture granularity is The reconstruction of the three component signals allows switching between spatial, temporal, and / or visual This may correspond to the granularity of switching between inter-point prediction modes. Reconstructing the issue to differentiate between spatial, temporal and / or inter-predictive modes Switching and operating ICP and second component based on first component signal The switching between signals is performed in units of prediction blocks or, using another expression, This can be done using a coding unit. Alternatively, using a transform block can be done.

[0010] ICP can be performed using linear prediction, where the IC of the data stream The signal of the P prediction parameter is transmitted by the reconstructed first component signal and the reconstructed The second component signal linearly participates in inter-component prediction at sub-picture granularity. The two weightings can be used to change the weights of the two solutions. The weighted sum of both components is used to obtain the inter-component prediction. in the data stream, one of which is the reconstructed Weighting for the first component signal and the reconstructed second component signal The other signal indicates the weighting of the other. However, linear prediction can be used to improve ICP prediction parameters while still achieving sufficient decorrelation. Meter signaling overhead can be kept at a reasonable cost. The prediction block unit is used to find the signaling or block in the data stream. The values ​​available for weighting may be distributed around zero. It can also contain zeros.

[0011] According to an embodiment, the ICP prediction parameter signaling outlined immediately above is This measure can include the transmission of conditional signals for the ICP prediction parameters. The signaling overhead associated with transmitting data signals is further reduced.

[0012] The weights are then coded using context modeling according to the sign. The signaling of the ICP prediction parameters is first coded with the absolute values ​​of the weights In a sense, this involves encoding the weights. By this procedure, if the absolute value is The probability of using a certain entropy for encoding / decoding depends on the code. and thereby improve the accuracy of the probabilities used. It all comes down to compression ratio.

[0013] According to an embodiment of the present invention, the inter-component prediction is a third inter-component method. Spatial, temporal and / or inter-view predictions used in reconstructing the component signals In other words, the inter-component prediction is applied to the prediction of the third component. A kind of first-order prediction compared to spatial, temporal and / or inter-component prediction of the input signal. It represents a two-stage prediction. Similarly, the reconstructed first component signal and the reconstructed The second component signal is the first and second component signals of a multi-component image or video signal. and the second component to perform spatial, temporal and / or can represent the prediction residual of inter-view prediction.

[0014] Inter-component prediction can be performed in the spatial or spectral domain.

[0015] According to another embodiment, the transmission of an explicit ICP source signal in the data stream is Used to switch between available ICP sources at sub-picture granularity. On the other hand, ICP is predicted by the method implemented for the signaling ICP source. Signaling of ICP prediction parameters in the data stream is used to adjust , where the entropy coding / decoding of the signal transmission of the explicit ICP source is The prediction performance of the prediction model is adjusted according to the transmission of the ICP prediction parameter signal at the second granularity. This measurement involves the use of a context model that depends on both parameters. The correlation between the transmission of signals, i.e., signals ICP source and signals ICP prediction parameters To reduce the signaling overhead by transmitting It can be used for.

[0016] According to a further embodiment, the reconstructed third component signal and the reconstructed third component signal are Swap signals in the data stream to swap two component signals For example, within an image, one sub-block may be the second chrominance Available luminance and first chrominance components for inter-component prediction For example, within one image, the transmission of the swap signal is Varying the order at sub-picture granularity in the second and third components. The other sub-blocks are used to predict the first chroma component. It has a luminance component and a second chrominance component.

[0017] According to an embodiment, encoding of an ICP source indicator for a particular block of an image are the ICP prediction parameters for the third and second components. For the transmission of the signal, the difference between the predicted parameters of the previously coded ICP is used. If the difference exceeds a certain limit, the ICP source indicator The ICP source indicator is not present for each block. The second component reconfigured as an ICP source for the three component signal In other words, the signal sent for the current block The predicted parameters of ICP are as follows: If the component signals are similar enough to ICP Source Indicator and Highly Indicative of Criteria for ICP for Components It can be assumed that the ICP prediction parameters are similar. Use the first component as the basis instead of the ICP for the second component. The second component is based on ICP, while the third component is based on ICP. The first case is more likely to occur in the case of RGB color components. and the second, more likely case occurs in the case of YCC color components. This measure shows that the coding efficiency is achieved by adding side information over ICP signaling. It can be increased by lowering the head.

[0018] Advantageous implementations of embodiments of the invention are the subject matter of the dependent claims. Preferred embodiments of the present invention are described below with reference to the drawings. [Brief explanation of the drawings]

[0019] [Figure 1] FIG. 1 shows a block diagram of a decoder according to an embodiment of the present application. [Figure 2] FIG. 2 shows a block diagram of a decoder according to an embodiment of the present application, applying ICP to inter-component prediction residuals. [Figure 3] FIG. 3 shows a block diagram of an encoder compatible with the decoder of FIG. 1 according to an embodiment. [Figure 4] FIG. 4 shows a block diagram of an encoder compatible with the decoder of FIG. 2 according to an embodiment. [Figure 5A] FIG. 5A shows a schematic diagram of an embodiment in which the transmission of a signal of multiple source ICPs can switch multiple source ICPs on / off. [Figure 5B] FIG. 5B shows a block diagram of an embodiment of a multi-source ICP module according to an embodiment in which the ICP signaling includes ICP prediction mode parameters in the form of weightings and ICP source indicators. [Figure 5C] FIG. 5C shows a block diagram of an embodiment of a multi-source ICP module according to an embodiment in which the ICP signaling includes an ICP prediction mode parameter in the form of a weighting per available ICP source. [Figure 5D] FIG. 5D shows a block diagram of an embodiment for a multi-source ICP module, with multi-source ICP performed in the spatial domain according to FIGS. 5B and 5C. [Figure 5E] FIG. 5E shows a block diagram of an embodiment for a multi-source ICP module, with multi-source ICP performed in the spatial domain according to FIGS. 5B and 5C. [Figure 5F] FIG. 5F shows a block diagram of an embodiment for a multi-source ICP module, with multi-source ICP performed in the spatial domain according to FIGS. 5B and 5C. [Figure 5G] FIG. 5G shows a block diagram of an embodiment for a multi-source ICP module, with multi-source ICP performed in the spatial domain according to FIGS. 5B and 5C. [Figure 6] FIG. 6 shows a flow diagram of processing of ICP parameter data in a decoder and encoder according to an embodiment in which the ICP parameter data for the third component includes weightings and source flags. [Figure 7]FIG. 7 shows a flow diagram of processing ICP parameter data for a third component according to an embodiment with weighting of a weighted sum of ICP sources for which ICP parameter data is available. [Figure 8] FIG. 8 shows a block diagram illustrating the processing of ICP parameter data for the second and third components when using swap components to improve ICP efficiency. [Figure 9] FIG. 9 shows a schematic diagram of an image to illustrate the possibility of signaling source flags and weightings at different granularities. DETAILED DESCRIPTION OF THE INVENTION

[0020] FIG. 1 shows a block diagram of a decoder according to an embodiment of the present application. The different components from the spatial data stream are shown with reference numeral 10. Constructed to decode multi-component video that samples scenes In particular, in the decoder 10, the data stream 12 is The input is a multi-component video signal that is reconstructed by decoding. 1 includes a time axis extending horizontally and a power output 14. By illustrating the images 18 belonging to one time, as shown in the image above, Thus, for each time instant, one image 18 is included for each of the three components A, B, and C. ,16 exemplifies multi-component video. However, It should be noted that there may be other components, as outlined above and further outlined below. Thus, components A, B and C are R, G and B or one luminance and two color components. Alternatively, however, the components may be color components such as Roma components. Components related to other wavelengths that exist outside the visible wavelength range, for example, Components may also be related to other characteristics of the scene. The components are not limited to frequencies or fractions of frequencies. , at least in part due to other physical parameters, such as for example reflectivity, etc. It can be related to the fact that Figure 1 shows that the images 18 of the different components are the same size, It suggests sampling the scene spatially accordingly with the same spatial resolution, but The time resolution may differ between components. The latter situation can also, in principle, The image rate can be adjusted to different resolutions between components A, B, and C. If not different, the term "image" is instead generally used to refer to a single It can be used to show samples of all components A to C at a time.

[0021] Internally, the decoder 10 extracts multi-component video 1 from the data stream 12. for reconstructing the first component signal 22 with respect to the first component A of 6 The first module 20 also includes a multi-component Reconstructing a second component signal 26 for a second component B of the video 16 a second module 24 for receiving the multi-component video signal; and a third module 25 for receiving the multi-component video signal. a module 28 for reconstructing a third component signal 30 relating to the component C; The latter module 28 includes a first component signal and a third component signal. The second component signal 22 and the second component signal 26 are used to reconstruct the first signal 30. To use inter-bit prediction, a signal is connected to the outputs of the first and second modules 20 and 24. The module 28 has a third component for the component C. To reconstruct the signal, the first and second components A and B of the signal 22 and 26 to improve the inter-component prediction used by module 28 This allows the decoder 10 of FIG. This increases the coding efficiency that can be achieved.

[0022] As will be outlined in more detail below, modules 24, 20 and 28 are actually , there exists one such hybrid system decoding branch for each component A, B and C. It can be part of the hybrid-based decoding branch. , coding branch 32 A The system includes a module 20 for receiving a first component from a data stream 12. Component A is reconstructed by encoding branch 32. B contains module 24 , and a decoding component configured to reconstruct component B from data stream 12. Gi 32 C includes a module 28 for regenerating a component C from the data stream 12. Such a decoding branch is shown by the dotted line 32. A , 32 B and 32 C to In particular, modules 20 and 24, as outlined in more detail below, and the first and second components are reconstructed and used for inter-component prediction in module 28. The two component signals 22 and 26 may in fact represent the prediction residuals. The constructed first component signal 22 is, for example, a branch 32 A By decrypting The prediction residual of the inter-component prediction performed by The computation performed by the module 20 based on the already reconstructed part of the image 18 The prediction residual of inter-component prediction can be expressed as a function of spatial and temporal Similarly, the second component signal 26 may be a multi-view and / or cross-view predicted signal. Decode branch 32 B The prediction residual for the cross-component prediction performed by That is, it can simply mean the already reconstructed image 18 of component B. We can express the prediction residual based only on the part of the Inter-prediction may be spatial, temporal, and / or inter-view prediction. The resulting third component signal 30 is then fed to a decoding branch 32. C By executing It can mean the prediction residual of the inter-component prediction. It can represent a prediction residual based only on the already reconstructed part of the image 18 of the first C. where this inter-component prediction also involves spatial, temporal, and / or Inter-view prediction may be used, i.e. spatial, temporal and / or inter-view prediction may be used. Regardless of whether the cross-view prediction performed in modules 20, 24, and 28 is performed, the prediction For example, the prediction mode may vary depending on the coding device or In other words, the prediction block, i.e., the respective coding device or data A sub-portion of the image 18 having a prediction mode used for signaling in the stream 12 The prediction modes are generally set for components A, B, and C, or or separately, or even more, on the one hand, the first component A, and separately, on the other hand For the second and third components B and C, signaling is performed in the data stream 12. Signaling this inter-component prediction in data stream 12. In addition, modules 20, 24 and 28 may be configured to receive component-specific signals. Receive prediction residual data. The prediction residual data may be in the form of transform coefficients of a spectral decomposition or or in the spatial domain, in the form of residual samples, and then transmit them to the data stream in the transform domain. When signals are sent in the spectral domain, inter-component prediction can be performed in the It may also be performed in the temporal and / or spectral domain. The 12 ICP region indicators vary the region over which inter-component prediction is performed. For example, in units of the prediction blocks or in units of the spectrum The ICP domain indicators are, for example, in units of the transform block for which the decomposition is performed. For example, you can vary the region in an image sequence, in a single image, or with sub-picture granularity. can.

[0023] Module 24 performs inter-component prediction, i.e., the output of module 20 is used to predict the The reconstructed first component is shown by the dashed branch leading to the input of rule 24. It will be explained later that inter-component prediction based on the component signal 20 can also be used. That is, the module 24 performs inter-component prediction within the component B. To receive the prediction residual for the first and second components, i.e., I of A to B, The signaled residual signal can be received as the prediction residual signal of CP prediction. P prediction is based on the first component signal 22 and is added to the third component C The second component signal 26 used by the module 28 for ICP is Based on the residual signal sent to component B, which is either combined or not yet combined This may be the result of 24 restructurings of the module.

[0024] Also, as outlined in more detail below, the prediction module 28 of the ICP can be supplied (and optionally by module 24) with parameters This parameterization may be, for example, a representation of the first and second component signals 22 and 26. Based on this, the first component signal 22, the second component signal 23, and the Regarding the selection among the third component signals 26 and their combinations, e.g. The first and second component signals 22 and 23 are used for ICP prediction of a signal or the like. 6 contributes to modifying the ICP of module 28 in the form of a weighted sum. Additionally, ICP signaling of multiple sources within a data stream is achieved by the ICP signaling in module 28. In addition to the first component signal 22 for Such multiple source ICs can signal their availability or unavailability. The signaling scope of P can be a complete video, a single image or time, or an image or time instance. It may relate to a slice or an array of slices or a sequence of slices.

[0025] The specific possibility is how the ICP of module 28 is How it can be parameterized and varied by sending signals The various embodiments discussed in this paper are further outlined. For ease of understanding, FIG. 2 shows an example of a decoder that illustrates a more specific implementation of the decoder of FIG. In the embodiment, the constituent signals 22, 26 and 30 are decoded into individual decoding branches 32. A ~3 2 C This is about the prediction residual of the inter-component prediction performed within the 3 and 4 show an embodiment of an encoder that is compatible with the embodiment of FIGS. 1 and 2. The various implementations related to adjusting the embodiments of FIGS. Details of example embodiments are described with respect to subsequent figures.

[0026] Figure 2 shows modules 20, 24, and 28, as well as inter-component prediction. vessel 34 A , 34 B and 34 C Three decoding branches 32 A ~32 C and, respectively, a combiner 36 that combines the component signals 22, 26, and 30; A , 36 B and 36 C and predictor 34 A , 34 B and 34 C The output of the inter-component prediction signal by the module 1, with outputs by means of the control signals 20, 24 and 28. Specifically, the decryption branch 32 A Inter-component predictor 34 A In order , regarding the reconstructed component A, i.e., the component A of the image of the video, The first component signal 22 is reconstructed to provide the sample value. Na36 A Inter-component prediction signal 40 A Components A, i.e. 38 A This is controlled via the inter-component prediction parameters for the module. As mentioned above, module 20 can be used to generate spatial or First component residual data 42 sent in the spectral domain A By Similarly, inter-component prediction 34 B Is that it? This is then combined into a reconstructed second component signal 26 output by module 24. The second inter-component predicted signal 40 is in turn combined by the B To determine In data stream 12, component B, i.e., 38 B Inter-component forecast The module 24 is controlled by the measurement parameters. A Localized like in the form of residual samples of a transformation applied to the spatial The second component can be present in the data stream 12 in the region Residual data 42 B However, according to the embodiment shown in FIG. , module 24 is applied in module 24 based on the first component signal 22 The inter-component predictions are then varied to change the inter-component predictions that are present in the data stream 12, i.e. Wachi, 44 B , for the second component, through the ICP parameter data, This option can be optionally omitted, as mentioned above. Then, module 24 combines signal 22 and data 26 to obtain a second component signal 26. Ta42 B the residual signal from component B, i.e., the residual signal from component B Then, it is the inter-component prediction for component B. and then, accordingly, obtain a sample of the second component of the image of the video. Combiner 26 B The second inter-component predicted signal 40 B Combined with do.

[0027] Decryption branch 32 B Similarly, a third component that decodes the decode branch 32C Inter-bit predictor 34 C performs inter-component prediction to obtain the inter-component predicted signal 40 C The inter-component prediction parameters present in the data stream 12 are used to derive 44 C which in turn is controlled via a third component signal 30. Combaina 26 C The third component in data stream 12 is The residual data 42C is used to determine the third component, i.e., Stream 12 of 44 C Controlled via inter-component parameter data for The first and second component signals are predicted by the inter-component prediction module 28. As an intra-prediction using inter-component prediction based on Nos. 22 and 26, The filter 28 produces a third component signal 30. Other combinations, such as multiplication, may be used. The combiner 36 can also be used A ~36 C The combination is illustrated in Figure 2. This can be done additionally, such as

[0028] As presented above, Figs. 3 and 4 are the equivalent of the corresponding encoders, i.e. Figs. 1 and 2. 3 shows an example of an encoder that is compatible with the decoder shown in FIG. The encoder 100 corresponds to the decoder 10. The encoder 100 is shown in FIG. In order to encode the same into the data stream 12, different components A, B and C to receive the video 16. The encoder 100 is configured to correspond to FIG. The 00 elements simply have the 100 added to the respective reference numbers of the corresponding elements in the decoder. using reference numbers that differ from those used for the decoder only in that Therefore, the encoder 100 of FIG. For each of the components A, B and C, a respective module, i.e. The data processing module 120 includes data processing modules 120, 124, and 128. for encoding a first component signal 22 into a stream 12, The code 124 is used to encode the second component signal 26 into the data stream 12. and module 128 adds a third component signal to data stream 12. 30, where module 128 encodes the first and second codes Inter-component prediction is used from component signals 22 and 26. As mentioned above, signals 22, 26 and 30 are residual signals, i.e., component-specific Coding branch 132 A , 132 B and 132 C The residual of the inter-component prediction performed within The difference signals can be represented respectively.

[0029] 4 is a more specific example of the encoder of FIG. 3 corresponding to the decoder of FIG. 2. Correspondingly, the encoder 100 of FIG. 4 generates three component-specific codes: Code branch 132 A , 132 B and 132 C and each of which contains a component Inter-company forecast 134 A , 134 B , 134 C and the residual former 136 A , 134 B , 134 C And that Each of the modules 120, 124, and 128 includes an inter-component prediction 134. A ~1 34 C As far as the predictors 34 are concerned, they are A ~34 C acts in the same way as These are inter-component prediction parameters38 A ~34 C The only difference is that there are differences in the components of each of the Video 16 Based on the already coded parts, each inter-component predicted signal 40 A , 40 B oh Call 40 C Predictor 34 A ~34 C While is controlled by the latter, e.g. , predictor 134 A ~134C Same thing in the rate / distortion optimization sense or anything else of that nature Then, adjust the residual shape 136 A ~136 C are the modules 120, respectively. , 124 and 128, which are lossy encoded into the data stream 12 To obtain the inter-component prediction signals 120, 124 and 130 of each first instruction, , inter-component prediction signal 40 A ~40 C and Video 16 and their respective components The prediction residuals are formed between the co-located parts. the difference signal 122, i.e. free from the coding losses introduced in module 120, The reconstructed version of the first command prediction residual signal 122 is added to the data stream 12 as a prediction residual. To encode the signal 126, we then use the modules as the basis for inter-component prediction. 22 used by module 124. As a result of the encoding, module 120 , first component residual data 42 A and then it generates a data Similarly, module 124 receives an inbound residual signal 126 As a result of encoding the second component residual data 42B and the ICP parameters Data 44 B which is then inserted into the data stream 12 Based on the latter data, a reconstructable version of the residual signal 126, i.e., together with the residual signal 22 to first order encoding the residual signal 130 into a data stream. The reconstructable version used by the module 128 for inter-component prediction The module 26 can be derived as a result of encoding the module 128. , module 128 is ICP parameter data 44 C and the respective residual data 42 C Output do.

[0030] After describing various embodiments of the decoder and encoder with reference to FIGS. 1-4, the modules The method of adapting the two-source ICP prediction performed by rules 28 and 128, respectively, is Regarding this, various embodiments are described that are related to various possibilities. A quick detour is to use H.264 as an example for hybrid video compression methods. 65 / HEVC, and benefits from two-source ICP prediction. For motivation, the entire discussion outlined below is limited to H.265 / HEVC extensions. Rather, the following explanations are merely exemplary and should be used to clarify the It only mentions H.265 / HEVC.

[0031] In the case of hybrid video compression schemes such as H.265 / HEVC, the prediction signal is temporally This occurs using spatial or inter-view prediction (predictive coding), and then the resulting The resulting prediction (called the residual) is transformed, quantized, and sent to the decoder (transcoding). Some entry points for Inter-Component Prediction (ICP) are For example, ICP can be applied on the first sample value. For the embodiments of -4, this means that the source of the ICP (i.e., signals 22 and 26) is required. This means that the residuals of inter-component prediction are not necessarily acceptable. , they may be directly related to the first source signal, i.e., video 16. In the spatial domain, or ICP is the original signal in the spectral domain, i.e., video 16 , i.e., on the transform coefficients of the spectral decomposition, e.g., the transform block of the image Transform coefficients such as DCT that are applied locally in units of , or wavelet transform coefficients For implementation and application efficiency reasons, the same To improve, however, the ICP may be described, for example, with reference to Figures 2 and 4 above. In this way, the inter-component prediction can be performed on the residual signal, as exemplified by For the method, affine prediction can be used for complex reasons. In the latter case, the only gradient of the prediction is ICP parameter data 44 B and 44 C Prediction parameters in the bitstream as part of However, in addition, as outlined below, The extension of the embodiment can be easily extended to affine transformations or more complex predictions.

[0032] The ICP approach for residuals using a linear predictor is usually as follows: I can state this with certainty. r'(x,y)=r B (x,y)+α×r0(x,y)

[0033] In the above equation, r'(x,y) is the spatial position (x,y),r B (x,y) component B is the final residual sample value for the position(x,y),r Bis the final residual sample value for component B of (x,y), That is, the prediction parameters for component B included in bitstream 44B Decoding / signaling for component B obtained from α and r0(x,y) and component A is located at the same spatial location in the prediction source. The reconstructed residual sample of r0(x,y) is B (x,y), i.e., signaling provides the residual of the computed component A. Note that α can be a floating-point value. It's lame.

[0034] See, for example, module 24 in the decoder embodiment. , using the residual signal 22 as the prediction source r0, and the ICP parameter data 44 B Among them, Sig Multiply the same using the nulled α and the component B, i.e., 26, That is, to extract the inter-component prediction residual for r', we use the residual data 42 B , sand Wachi, r B Module 24 in that it adds a signaled residual signal derived from ICP can be applied.

[0035] For purposes of implementation, floating point values ​​can be mapped to integer values. For example: The floating-point value α may be allowed to range between -1 and 1, inclusive. Using three bits of precision, the formula can be rewritten as: r'(x,y)=r B (x,y)+(α×r0(x,y))≫3

[0036] The right shift operation is a division by 2 to an exact power of 3. Hence, the floating-point α can take the following integer values: α∈[0,±1,±2,±3,±4,±5,±6,±7,±8]

[0037] Also, for practical purposes, α can be limited to the following value: α∈[0,±1,±2,±4,±8]

[0038] That is, the final mapping allows, for example, a decoder or more specifically a module Rule 24 is α d By using The bit stream, that is, the ICP parameter data of the data stream 12, 44B, which is the decoded value from α=1≪α d

[0039] The ICP approach described above as representative for module 24 is e.g. The first facet is The first facet specifies the prediction source, the second facet specifies the prediction model, and the third and final facet specifies the prediction source. The template specifies the ICP prediction parameters or, more specifically, the prediction model parameters. Considering the above formula, the forecast source is r0, then the forecast model is is a linear predictor using the same spatial location of the source components as The parameter is α.

[0040] There is a strong dependency between the second and third facets / modules. An example of dependency is again the input, but with another component: the prediction source. In this example, a linear predictor using the same spatial location would be used. Due to the limitations on measurements, only one predictor (model) parameter is required, so this is a single Only the prediction parameters of α, i.e., α, need to be transmitted in the bitstream. There is also an interaction between the source and the prediction model. Typically, the luminance residual is used as a prediction source. This is the case when, for example, luminance is used as component A. and for the first chroma component as component B. However, all available components are used as a forecast source. uses the appropriate prediction, i.e., the prediction that includes samples from both components This is the case for module 28. This module is available Two components, i.e., components A and B, are used as two forecast sources, i.e., That is, for components A and B, the same example is used for the luminance component and the first chrominance component. For example, linear prediction requires two model parameters instead. To be more accurate, the linear prediction that can be used for module 28 is: It can be defined as follows: r''(x,y)=r C (x,y)+α0×r0(x,y)+α1×r1(x,y)

[0041] Thus, as far as module 28 is concerned, two prediction sources are available: Signals 22 and 26 are r0 and r1, respectively. That is, the module 28 for ICP detects the co-located portions of the signals 22 and 26. Now, ICP has predicted the signal 30, i.e., the r' portion. The remaining data 42 C , i.e., rC As can be seen from the figure, the module 28 The co-located parts of the signal 22 weighted by α0 and the signal 23 weighted by α1 are The weighted sum of signals 26 weighted by the signal is modified by adding a signaled residual. It is used as a weighted sum.

[0042] As far as the relationship between modules 28 and 24 is concerned, the following is noted: As indicated by ICP prediction and transmitted second component residual data 42 B By combining with ICP can be used on the basis of the second component signal that is obtained. That is, r' is the basis of the ICP performed by module 28, i.e., one prediction That is, r' can be used as r1. However, as also described above, according to an option, module 24 does not use ICP. In that case, in Figures 2 and 4, on the one hand, the output of module 20 and module 2 4, on the other hand, is excluded (or between modules 120 and 124). In that case, r1 is B In a further embodiment, r1 is based on component A. Despite the use of ICP in module 26, B The point that it is chosen because it is equal to 2 and 4 can be modified. In that case, the module The arrows leading from module 24 to module 28 indicate the outputs other than those leading to combiner 36B. It starts from the further output of module 24.

[0043] Thus, according to the embodiment outlined above, the possibility exists to create multiple predictive solutions for ICP. The ICP method is provided for use with a 32-bit 8-bit JPEG file, where the performance characteristics of the ICP method are such that it provides a higher compression efficiency. In the following, various details are The following discussion will be presented with respect to a general multiple prediction source ICP. It deals with global signaling, possibly source ICP. According to such an embodiment, local signaling of multiple source ICPs is addressed. Multiple source ICP, image and video compression applications with additional dependencies Further techniques are described that allow for high efficiency for

[0044] A kind of global signaling of multiple sources for ICP is multiple source IC Multiple Source ICP includes the possibility that the P method can be turned on or off. is allowed using a global flag sent at the appropriate level, even if If so, a further bit or series of bits is transmitted, since each transforms each predictor or encoder and signals its use. The global flag indicates that the transmission of a type of multiple source ICP signal in a data stream is A set of I including the source ICP coding mode and at least one non-ICP coding mode This shows the switching between various ICP coding modes. There are also various source ICP coding modes possible, e.g., ICP They differ in their domains, i.e., spatial or spectral domains, and other adjustment capabilities. Therefore, the global flags further define the forecast model with respect to one or more forecast parameters. It can be a single bit or a series of bits specifying the A bit or series of bits is generated by a block or each predictor or encoder. and in the case of multiple source ICPs allowed, change the ICP parameters. Metadata 44 C Examples for this are possible.

[0045] Global flags are used to set parameters in H.265 / HEVC or Set the sequence parameters such as the image parameters to be set. It can be transmitted in the sequence or even in the slice header. depends on the use of additional tools, e.g., for tile or wavefront processing, both Even different levels of signaling for parallel processing are possible. The source ICP can be enabled for the entire video sequence, but There may be invalidation of certain content within the service. The global flags in the sequence parameter set are, for example, This will overwrite the flag.

[0046] Thus, in summary, according to this embodiment, the decoder 10 is a multi-component For different ICP mode portions 202 of source video 16, multiple source ICP encoding modes are used. ICP coding modes and a set of ICP coding modes including ICP and non-ICP coding modes The encoder 100 inserts the signal into the data stream 12 so that the signal is switched between It may be configured to respond to the signal transmission 200 of multiple source ICPs.

[0047] According to the multi-source ICP coding mode, inter-component prediction is performed when the signal is transmitted digitally. In Data Stream 12, explicitly or implicitly, the first and second The signals of the spatially corresponding portions 204 and 206 of the component signals 22 and 26 are Nulled or multiple source ICP encoding modes is calculated based on a combination, such as a weighted sum, of spatially corresponding portions 204 and 206. The third component signal 30 of the component C is predicted by the inter-component prediction. For more accuracy, if multiple source ICP coding modes are available, see Figure 1. 5A Multiple Source ICP Signaling 200 for the Intermediate ICP Mode Portion of Video 16 In that case, for example, modules 28 and 128 are respectively Then, ICP for each block of component C can be executed. It may be, for example, a predicted block or the like. Metadata 44 C Each block 208 is either a spatially corresponding part 204 or an empty space. Whether or not it is inter-component prediction from the inter-corresponding part 206 is determined. Alternatively, the image block within the intermediate portion 202 may be At block 208, the third component signal 30 is a combination of both portions 204 and 206. Then, each portion 208 is predicted from the sum of the blocks 20 The weighting of the weighted sum of parts 204 and 206 gives the inter-component prediction for 8. With respect to the weighting factors α0 and α1, which indicate the weighting, the co-located parts 204 and 206, a method for predicting components from ICP parameter data 44 C can be shown.

[0048] In non-ICP coding modes, inter-component prediction is performed by each ICP mode unit 20 Therefore, for such ICP mode parts, ICP Parameter data 44 C does not need to be present in the data stream 12. Alternatively, For such an ICP mode unit 202, inter-component prediction is performed for component A. and B, by the respective modules 28 and 128. For example, the block of the non-ICP coding mode unit 202 can be Block 208 is the I predicted from co-located block 204 of component A. Alternatively, the entire block 208 may be a CP. However, the prediction between blocks 208 may be inter-component prediction from block 206. Switching is not possible. That is, all of the blocks 20 within the portion 202 8 is also an inter-component prediction from block 204 of component A. Or, All blocks 208 within portion 202 are located at the same position in component B. 2. The inter-component prediction is from block 206 located at

[0049] As already mentioned above, the ICP mode unit 202 can process image sequences, individual images, or a slice, or a series of slices. As mentioned above, multiple source ICP For ICP mode section 202 in which coding mode is enabled, the ICP parameter data is 44 C includes, for example, two weighting factors α0 and α1 for portion 208. On the other hand, for ICP mode unit 202 in which a non-ICP encoding mode is active, ICP Parameter data 44 C Alternatively, the ICP parameters for block 208 are not present. Data signal 44 C is simply the case where only one of the weighting factors α0 and α1 is It is set to zero for all blocks 208 within this portion 202 .

[0050] Several possibilities exist for multiple source local signaling for ICP. For example, if multiple source ICPs are used, the decision 210 for the forecast source may be As can be seen in Figure 5B, the ICP data C It can be sent locally as part of the For example, components A, B and C may be, for example, luma, first chroma and second Then, the ICP parameter data 44 C is a component Whether the inter-prediction is for the luma, i.e., A, or the first chroma component, i.e., B, Each block 208 includes a flag 210 indicating: It may be a coding block, a prediction block or a transformation block. For example, the parameter 38 of the inter-component prediction C However, there is a switch between spatial and temporal prediction. The predicted block is the inter-component prediction parameter 38 C But, The type of prediction and related information that is signaled for the coding block of which each prediction block is a part. It may also be a block that signals or changes associated prediction parameters. , if spatial prediction is signaled for the coding block, The prediction parameters for the coding block are Blocks are spatially predicted from adjacent already decoded / encoded parts of component C. The signal can be generated along the spatial direction in which the signal is to be transmitted. The temporal prediction mode signaled for the coding block to which the prediction block belongs is generated. In this case, the predicted block can signal a motion vector as a prediction parameter. The transform block is a function of the inter-component prediction for component C, which is performed by the spectral decomposition. In this case, the source for prediction is either luminance or primary A flag 210 indicating whether the chroma component of the Could it be independent of the ICP prediction parameters 212, e.g., the prediction weight α? It is important to note that the components that make up the ICP forecast source For component A, α0 is used, and for component B, which forms the ICP forecast source, In this case, α1 is used as the weighting. The forecast source is always weighted as follows: For example, dependencies are given when signaled after the parameter(s). On the other hand, the source always uses the flag 210 for the predicted or coded block. However, when the ICP prediction parameter 2 is 12 is transmitted per transform block.

[0051] Considering the above example, a block in component C, such as flag 210, indicating the prediction source, 208, e.g., to convert a block of the second chroma component. The ICP prediction source may be transmitted only for the purpose of While not equal to, ICP parameter data 44C is signaled within the range of For CP predictions only, as part of the ICP parameter data 44C, The ICP prediction can be signaled to the block of component C. This means that the condition for multiple sources must be met. There are two situations where the condition is given: the first component, say the luminance component, and the second component When each transform block of a component, e.g., the first chroma component, inherits the residual The first situation occurs: the first chroma component contains only zero-value residual values, while the luma transform block The second situation is given when the block inherits the residual. However, the luminance is It is predicted from the

[0052] The fixed context model is not used due to the flag 210 indicating the ICP prediction source. Dependence on the situation where multiple sources occur can also be used in two different contexts. Furthermore, other I models such as weighting are possible. Depending on the CP prediction parameter(s) 212, there may be, for example, a negative α may result in a different context model than positive α. Another possibility is that In this example, an absolute value of α greater than 2 means that α is equal to or less than 2. This results in a different usage of the context model than if

[0053] Therefore, for example, as shown in the example illustrated in FIG. 6, the ICP prediction data 44C is conditioned by the ICP source indicator 210 and is calculated as an ICP parameter 212. Component C. 6, in response to modules 28 and 128, respectively, in step 220, IC P parameter data 44 C Read / write α to / from the byte. And if α is actually zero, If α is equal to zero, check if 222 is true. CP parameter data 44 C are further ICP parameters for this block 208 As shown in 224, the ICP contains either component A or B. However, if α is not zero, then ICP parameter data 44C is the ICP parameter data in step 226 or 228. ICP prediction source as source flag 212 read from or written to 44C or includes a signal for block 208.

[0054] For illustrative purposes, FIG. 6 shows the relationship between α in step 220 and the predetermined criteria. Depending on the context, different flags are used for entropy coding / decoding. This indicates the possibility of being used for the following purposes, and the situation is checked in 229. If the absolute value of α is greater than a predetermined value, for example, 2, or if α is negative or equal, However, as already mentioned above, the criterion may be satisfied regardless of whether The dependency of the context used to decode / encode the base flag is simply optional. and accordingly steps 229 and 228 may be omitted according to an alternative embodiment. Regardless of whether steps 226 or 228 apply. For α different from zero, in the case of ICP prediction, α0 is the first component A. and ICP is performed using α in step 220, or the ICP prediction software In the case of the source, α1 is the source flag and the second component B of step 230 This shows:

[0055] Thus, summarizing FIG. 6, the ICP parameter data 44C is 8, i.e., 212, block 208 (i.e., 21 2) can have one weight α coded into the The coding may require spatial prediction based on the α of neighboring blocks. The parameter data 44C is used to calculate the parameter α for block 208. 8 may have a source flag 210 encoded in the data stream 12, The encoding of may include entropy coding, and may include a specific context-adaptive entropy coding. Then, we encode the current block 208 using a context that depends on α. Therefore, steps 226 and 228 are performed to implement a context-adaptive encoding. Step 230 can include tropy encoding / decoding of the above α0 and α1. The application of a confirmed method is required. The other of α0 and α1 is set to zero, for example. will be done.

[0056] The extended ICP technique is described next. In particular, multiple sources are used for component C. When available, as in the case of ICP prediction, the possible ICP predictions are Both components A and B can be accepted. In this case, the ICP prediction parameters 212 are the result of the linear combination of each component as described above. Depending on the result, the weighting of the two ICP predictions must be specified.

[0057] Figures 5c and 7 show that the ICP parameter data 44C are obtained from the above confirmed equations, respectively. The same applies in step 236 according to the steps 232 and 234. Each block 208 to be read / written contains two weights α0 and α1. , exemplifies the possibility of transmitting a signal.

[0058] For the sake of completeness, Figures 5D-5G already show the situation described above. The ICP of 28 Joules is the residual signal at 42C in the spectral domain or In the spatial domain by signaled components C, i.e., transform coefficients, e.g. For example, in the form of DCT coefficients or other transform coefficients of a transform block or the like. Performing spatial domain multiple source ICP can be performed as shown in Figures 5B and 5C. 5D and 5E, respectively, using the module 28 of the embodiment , is illustrated as a base. As shown, signals 24 and 22 are spatially The samples arrive in a corresponding manner, i.e., at the same positions. are multiplied by the weights α0 and α1 and then summed together, i.e., The samples are then concatenated to give the signal 30 using the transform coefficients 42. C Apply to the top By performing multiple source ICP in the spectral domain, and respectively, again using the example modules of Figures 5B and 5C as a basis. 5F and 5G, where signals 24 and and 22 can be reached in a manner that they are spatially coincident, i.e., located at the same position. The samples are given in the following order: To obtain the same spectral resolution, i.e., to change the coefficients, or and 24 already arrive in the transformation domain. The transformation 217, for example, In case of misalignment of the transformation blocks between C and B and C, respectively, it is necessary The coefficients of signals 20 and 24 are multiplied by weights α0 and α1, respectively, to obtain And each corresponds to a spectrum, 42 C You can get it from The summed coefficients are then summed to give the signal 30. To obtain the result, the inverse transformation 216 is performed.

[0059] A further approach to improving compression efficiency is component swapping for ICP. According to this method, syntax elements are signaled within the ICP parameter data 44C. Then, we can identify the correct order of the residuals. In this example, we have three transformation blocks. A block, for example, has spatially corresponding parts, one for each component A, B, and C. The ICP is then rebuilt for the first and second components. It is also possible to exchange components or even the first and third components. This adaptive component makes particular sense in combination with ICP and multiple source ICPs. The switch allows for lower prelude costs and reduced energy. For example, In this example, the application allows switching between two chroma components B and C. In the example, two chroma components B and C from the luminance, i.e., component A The prediction results in the same cost, but the second one using the first chroma component. Chroma component prediction requires more overhead but uses the second chroma component. Prediction of the first chroma component requires fewer bits and results in lower cost.

[0060] This is again shown in Figure 8, which shows the first, second, and third components Residual data of 42 A , 42 B and 42 C are steps 240, 242 and 243, respectively. 44 indicates that it is being read / written. ICP by 28, 124 and 128 respectively, i.e., 246 signal swapping 248, the weight for ICP performed on the basis of the first component, i.e., α Includes 44 ICP parameter data B and 44 C And it is controlled by , ICP parameter data for the second component 44 B and the second and third The weights used for ICP between the components, i.e., the weights for the third component ICP parameter data for 44 C α1 is obtained from the swap signal In response, the transmitted residual signal 42 A ~42 CFollow the continuous or dashed lines to ICP246 As can be seen from the figure, the second component signal 26 is Therefore, the first or third component can be used as the basis for the swap signaling. Similarly, a third component signal 30 is obtained in response to the first component signal 30 by ICP. It is obtained on the basis of the first component or the second component. In the non-exchanged case, the weights α and α1 of the ICP parameter data are that is, they remain the same as the second component signal 26 and the third component signal 27. However, the ICP predictions of the component signals 30 are not shown by the dashed lines. In the exchanged case, the weights α and α1 of the ICP parameter data are respectively: Reinterpreted to control for first and second stage ICP predictions. The weights α of the P parameter data are referred to the first stage ICP, and the ICP parameters are The metadata weight α1 is referred to the first stage ICP. If not exchanged, The interpretation does not change anything. However, in the swapped case, the third component signal 3 0 is an inter-component prediction that is predicted before the second component signal 26. As a result, the ICP parameter data weight α1 is effectively It is used for inter-component prediction, which predicts the In this state, as far as inter-component prediction is concerned, the second component B is It takes on the role of the third component C and vice versa.

[0061] Data 44 C The weight α1 of the ICP parameter data is used to calculate the weight of the ICP parameter data. parameter data weights α0 or source indicator 212. Note that the embodiment of FIG. 8 can be combined with the previous one. C refers to the second stage ICP, i.e., the second component where the signal undergoes ICP. For the case, this is reinterpreted as signal 26 or 30. Two sources is available in both cases, regardless of the swap signaling 248. And ICP The parameter data weight α0 is based on component A in both cases and is used to calculate the ICP. It can be used to control the components A and B in the non-interchanged case. and B, and between components A and C of the replaced case, respectively. Alternatively, the source indicator can be interpreted.

[0062] Furthermore, in a method similar to that shown in FIG. 8, the switching flag is used to change the color space, i.e., It is possible to change the switching between components by signaling a flag. For each component, the ICP prediction parameter α0 or α1 is transmitted. Additionally, the color region change flag indicates whether the color region is to be changed. If it does not change, the second and third components B and C reveals two saturation components, e.g., α0 or Component A is predicted individually from A using α1. However, for example, color changes may occur. If the two are predicted individually from A using α0 or α1, then B and C are predicted individually from A using α0 or α1, respectively. They are then generally subjected to a transformation to change color spaces, which may For example, converting an ABC color space linearly to a YCC color space. Only when a change occurs between A and B that is not predicted from A, for example, a color space change occurs. It is virtually predicted from cases A and C. Alternatively, the signaled color space ABC can be converted to YCC Two or more color transformations mapping to a color space may be available. In this way, various localized In this method, the color space in which the ABC components are transmitted may vary between two or more color spaces. and, as signaled by transmitting 248 a signal for YCC. The change in the color is not a change between the color transformation. The data signal is transmitted in a data stream of a coding device that is larger than the unit at which the data signal is transmitted. And for example, it transforms the block. Thus, α0 or α1 For components B and C, they are transmitted in the first block as a transform block. Residual survey sent for B B is r B '=r B +α0·r A For component A according to Residue sent to A And similarly, the residual r C teeth, r B '=r B +α1·r A Follow A The prediction residual signal (22, 26, 30) is combined as follows: For simplicity, we denote it as T, or directly as the YCC prediction residual signal, i.e., (r Y ,r C1,r C2 ) T =T·(r A ,r B ',rC') T or (r Y ,r C1 ,r C2 ) T =(r A , r B ',r C ') T By using the residual of either It is obtained by a color transformation, which can be similar to an RGB transformation. Whether or not the signal is transmitted is controlled via signal transmission 248. TIFF2025183207000002.tif15142

[0063] The aforementioned data 44 B or 44 C ICP prediction parameter α or α0 or α1 in The encoding is as above, using integer nominator signaling with small weights. It can be coded or even improved further. When applied in color space, the value of α is typically either α or α0 or α1. It is used for either, and is mainly a positive relatively large value, i.e., with floating-point precision, 1 or 0.5. On the other hand, Y'C b C r Therefore, the value of α is often set to zero. The asymmetric mapping and α regulation can further improve the efficiency in terms of compression ratio. can be used to improve the α mapping. is. α∈{0,±1,±2,+4,+8} or α∈{0,±1,+2,+4,+8}

[0064] Note that it identifies the maximum allowed value of α in order, and the sign of α is If the instructions are unrelated in a symmetric mapping, then all That is, the symbol can be transmitted after transmission of the absolute value of α. Furthermore, the absolute value of α is , to account for different probability distributions for the frequency of occurrence of positive and negative values ​​of α, Entropy coding / decoding using context modeling accordingly - Patent Application 20070122997 It could be.

[0065] Some of the following embodiments are more specific.

[0066] According to an embodiment, for example, in the case of two prediction sources, it is Since it was a case of After that, which forecast source should be used is determined by flag 210 (source in Figure 6 above). For this example, the predicted source flag 2 is transmitted. 10 is only necessary when predictions must be applied. And it is IC P can be derived from the predicted parameters.

[0067] In a further aspect, each block 208, e.g., each of the predicted blocks From the specific ICP prediction parameters 212 of the nested transform block, The source flag 210 indicates which prediction source should be used for each prediction unit. In this preferred embodiment, the I such as α of the predicted block level is always transmitted. It should be noted that it is also possible to transmit CP prediction parameters 212 .

[0068] In another preferred embodiment of the present invention, nested transformations of each coding block are The flags pointing to the specific forecast parameters of the conversion block indicate which forecast source is used. The source (i.e., source flag) must always be sent for each coding block. In this preferred embodiment, the prediction block level or the coding block level It should be noted that it is also possible to transmit ICP prediction parameters.

[0069] Figure 9 illustrates the possibilities just outlined as an example. In particular, as mentioned above, ICP The parameter data 44C includes two components: ICP prediction parameters 2 12, for example, can include a weight α and an unconditionally encoded ICP source flag 210. As already shown in FIG. 6, steps 220 and 222 are executed as outlined above. Steps 226, 228 and 229 are rearranged to be located between the two. In this case, steps 228 and 229 may even be ignored. 9, the ICP parameter data 44C is the accuracy signaled by the ICP prediction source. This illustrates the possibility that the accuracy is coarser than the accuracy with which the ICP prediction parameter α is transmitted. The ICP source flags shown by the continuous lines in FIG. 9 are sent in units of blocks 250. The ICP prediction parameter α is transmitted as the ICP prediction parameter data 44C. , sub-blocks 252, i.e., subdivisions of block 250. 1 illustrates blocks 250 and 252 of a rectangular image 18, and also illustrates blocks of other shapes. It should be noted that the `.c` can be used in a similar manner.

[0070] In a further embodiment, the source flags 210 indicating the prediction source are respectively The ICP prediction parameters 212 can be linked to the weights, i.e., the current The ICP prediction parameters to be set are the block or current prediction block or current code In this embodiment, the source flag 2 indicates the prediction source. For linear prediction, the only prediction parameter is the range between 0.25 and +0.25 (or or the range -2 and +2 for α with integer values, or for more precision , an integer is encoded only if its nominator is evaluated, but all inclusively. For example, see Figure 6, where the ICP parameters or data 44C are , it is necessary to decode the source flag only if α is different from zero. Alternatively, the source flags can be set to a specific range of values ​​for α (e.g., -0.25 to +0.25). Just in case there is something mentioned above, both are inclusive and specific blogs. For locking, ICP parameter data 44 C If α is If it is out of range, the source flag is not sent explicitly in the data stream, The first component A is not estimated, for example, to be referred to as the ICP prediction source. For example, component A is the luminance component, and components B and C are the two If it is a chroma component, a large absolute value of α will result in a prediction source for the second chroma component C. is the luminance component rather than the other first chroma component B. In Figure 6, a further check is made to see if α needs to transmit / read the source flag. It checks if it is within the range of values ​​and lies between 222 and 229. If not, the source flags are not read / written, otherwise step 2 29 is accessed.

[0071] In another embodiment, the source flag indicating the prediction source is the IC of the first chroma component. In this example, the ICP parameter data 44B, i.e., That is, in the case of linear predictors for the co-located blocks of α, only one ICP predictor is used. The measured parameter is between -0.25 and +0.25 or between -0.2 and +0.2. When the value range may be chosen differently, both are considered inclusive and predictable. ICP parameter data showing the measurement source 44 C The source flags are, for example, For example, a check can be added to Figure 7. According to ICP parameter data 44 B are the blocks placed at the same position The inter-component prediction of component B is performed using the weight α. It is checked whether to display for the block placed at the position, and its size If the size exceeds some predetermined value, for example, Components A, B, and C indicate that the third component, C, must probably be an ICP. This is the case when the second component, i.e., the estimated first chroma component, is used as the basis. In this case, once the source flag is estimated, the second component is set to I Used as an indication that a color space such as YCC is supported to identify the CP prediction source. However, the size of α for co-locating blocks is If so, parameter data 44 B is smaller than a predetermined value. As shown by the source flag, the current block is included as part of the ICP parameter data. Signal 44 for lock C will be sent.

[0072] According to an embodiment, the context model for the flag indicating the prediction source is IC P is independent of prediction parameters, e.g., weightings. Therefore, one fixed context This is the case, for example, with respect to the description of FIG. can be ignored by the yes pass of check 222 which directly leads to 226 This means that

[0073] However, in another embodiment, the context model for the source flags is It depends on the ICP prediction parameters, e.g. weighting. When linear prediction methods are used, only For example, different context models can be used for one prediction parameter: , the weights are, as shown above, for prediction parameters with integer values, e.g., -2 and Both 1 and 2 are inclusive ranges.

[0074] Furthermore, in the case of linear predictors, if the only ICP predictor parameter is negative, then The following context models can be used, which were also mentioned above:

[0075] The use of multiple prediction sources can be achieved, for example, by setting the sequence parameter set. It can be turned on / off using a flag sent with As discussed above with respect to FIG. 5, transmission, however, in the picture parameter set, Or it can occur in the slice header.

[0076] The usage of multiple forecast sources can be specified at different hierarchical levels. For example, it is particularly important to consider the sequence parameter set and the image parameter set. Since the image parameter set flag is low, this preferred embodiment Possibility to disable multiple source ICP for an image or frame of a video sequence In a further aspect, the prediction source, i.e., the source flag, is indicated. The flags are the ICP prediction parameters of the current and previous components, For example, the weights of the ICP prediction parameters may depend on the relative differences in weighting. If the relative difference is greater than a predetermined limit, the flag is set to, for example, 1. In other words, in the case of Figure 6, the additional check is A ream check 222 is applied, where the ICP parameter data 44 B By The weight associated with the co-located block is greater than a predetermined amount. For the current block, ICP parameter data 44 C Whether it is different from the α of Regardless, it is checked with this additional check. If yes, this Components A to C are related to each other as in the YCC color space. The source flag specifies a specific first chroma component, i.e., component B. The implication is that it can be inferred that the ICP source for C's ICP is identified, This can be interpreted as otherwise the source flags are read / written. In other words, data44 C In response to transmitting 212 the ICP prediction parameter signal Therefore, the third component prediction parameter α can be varied at sub-picture granularity. Similarly, the second component signal 44 B ICP prediction parameter signal for The component prediction parameter α varies with sub-picture granularity. Thus, the weighting is ICP for component B and ICP for component C. There may be local differences between the multi-source ICPs. Thus, the check is component and third component prediction parameters differ by more than a predetermined limit In this case, for example, the difference or index of α values ​​can be used as the standard of deviation. For locations where the above limitations are exceeded, the ICP source indicator 210 , otherwise, it may be inferred, but for places where they do not differ beyond a limit To do this, the ICP source indicator 210 C may be present in

[0077] If multiple forecast sources are available, further According to an embodiment, the prediction parameter(s) of the ICP are determined by the two prediction sources. Predictions that support weighted combinations can be identified and transmitted.

[0078] According to a further embodiment, linear prediction is used for multiple source ICP, and IC In this embodiment, the only absolute ICP prediction parameter is The data is binarized and encoded using an abbreviated singleton code, and the signature The signature may be coded first, and the only prediction parameter is Depending on the sign of the data, different context models are used for the binary decomposition bins. According to a further embodiment, the signature is first coded. A signature coded in the desired implementation, i.e., the parameters are executed differently. According to the prediction quantization, the maximum allowed prediction parameter is between 0.25 and 1, both All of this could be included in the scope of inclusion.

[0079] According to an embodiment, the flag indicates whether the second and third components are swapped, This was outlined above with respect to FIG. 8. In this embodiment, the first The residual constructed for the transform block associated with the chroma component is the residual of the second component. can be treated as a difference and vice versa.

[0080] With respect to the above description of specific embodiments, it is understood that the same is applicable to multi-component image encoding. Note that this is easily transferable.

[0081] Although some aspects have been described in the context of a device, these aspects may also be used in block diagrams. The method description may be a method or apparatus that corresponds to a method step or feature of a method step. Similarly, aspects described in the context of method steps are also A block or item description or corresponding device feature. Part or all of the software may be based on (or use) a hardware device such as a microprocessor. Thus, a programmable computer or electronic circuit can be implemented. In some embodiments, one or more of the most important method steps may be performed by such an apparatus. It can be executed.

[0082] The coded image or video signal of the invention can be stored on a digital storage medium. or a transmission medium, e.g., a wireless transmission medium, or a wired transmission medium, e.g., It can be sent over the Internet.

[0083] Depending on the particular implementation requirements, embodiments of the invention may be implemented in hardware or in software. The implementation may be implemented in electronically readable control files stored thereon. Digital storage media with control signals, such as floppy disks, DVDs, Blu-rays, Using CD, ROM, PROM, EPROM, EEPROM or FLASH memory It can be executed. And it can be executed by the program. cooperates (or is capable of cooperating) with a computer system capable of The digital storage medium may be computer readable.

[0084] In some embodiments of the present invention, a method for carrying out any of the methods described herein is provided. An electronically readable code capable of cooperating with a programmable computer system A data storage medium having a control signal is included.

[0085] Generally, embodiments of the present invention are implemented as a computer program product having program code. The program code can be implemented to perform one of the methods. Therefore, when a computer program product runs on a computer, it is implemented. The gram code may for example be stored on a machine-readable carrier.

[0086] Other embodiments include any of the methods described herein and stored on a machine readable carrier. The present invention also includes a computer program for carrying out one of the methods described herein.

[0087] In other words, an embodiment of the method of the invention is therefore the method described herein. is a computer program having a program code for executing one of At that time, the computer program runs on the computer.

[0088] Thus, further embodiments of the inventive method are described herein. a data carrier (or digital device) containing a computer program for carrying out one of the methods (data storage medium or computer readable medium). Storage media or recorded media are typically tangible and / or non-transitive.

[0089] A further embodiment of the inventive method therefore comprises carrying out one of the methods described herein. It is a data stream or series of signals representing a computer program for A data stream or sequence of signals may be transmitted, for example, over the Internet. For example, it can be configured via a data communication connection.

[0090] Further embodiments may be implemented, for example, in a computer or programmable logic device. A processor configured or adapted to perform any of the methods described herein. Includes means of management.

[0091] In a further embodiment, a computer for performing any of the methods described herein is provided. This includes computers on which the program is installed.

[0092] A further embodiment of the present invention is a computer program product for performing one of the methods described herein. configured to transfer (e.g., electronically or optically) a data program to a receiver. The receiver may be, for example, a computer, a mobile device, The device or system may be, for example, a computer to a receiver. It may include a file server for transporting computer programs.

[0093] In some embodiments, some of the functionality of the methods described herein may be achieved. or all of the above, a programmable logic device (e.g., a field program) In some embodiments, the present invention may be applied to a wide variety of devices, including a wide variety of gate arrays (e.g., a gate array capable of performing a wide variety of functions). Field programmable to perform one of the methods described herein. Such a gate array can cooperate with a microprocessor. The method is preferably also implemented by a hardware device comprising:

[0094] The devices described herein may use hardware devices or may be computer-based. Use a computer or a combination of hardware and computer This can be implemented.

[0095] The methods described herein may be implemented using hardware devices or computers. Use a computer or a combination of hardware and computer It can be executed.

[0096] The above described embodiments are merely illustrative for the principles of the present invention. It is understood that variations and details of modifications and arrangements will be apparent to those skilled in the art. Therefore, the scope of the examples in this specification is not limited to the scope of the claims that follow. It is intended to be limited to the specific details presented for purposes of description and illustration.

Claims

1. A first image or video (16) from the data stream (12) reconstructing the first component signal (22) in terms of the components (A) of The multi-component image or video ( Reconstructing the second component signal (26) in terms of the second component (B) of Build, The reconstructed first component signal (22) and the reconstructed second component signal (23) are The multi-component signal (26) is obtained by using inter-component prediction. A third component (C) relating to the image or the third component of said video (16) By reconstructing the input signal (30), Sampling the scene for spatially distinct components and a decoder configured to decode the component image or the video (16).

2. The decoder selects a set of ICP coding modes in the data stream (12). Between the ICP encoding modes, different ICP mode portions of the multi-component image or transmitting multiple source ICP signals (200) to switch for video (16). configured to respond to Multiple source ICP coding modes; At least one of the non-ICP encoding mode and the fixed one-source ICP encoding mode. Also includes one and The plurality of source ICP coding modes are signaled to the decoder, Alternatively, a spatially corresponding portion of the reconstructed first component signal and the reconstructed The inter-component prediction is performed by combining the second component signal with the first component signal. a current sub-portion of a current image of said multi-component image or video, configured to reconstruct three component signals (30); The non-ICP coding modes are those in which the decoder does not use any inter-component prediction. of the current sub-portion of the current image of the multi-component image or video that is not configured to reconstruct the third component signal (30); The fixed single source ICP coding mode allows the decoder to the fixed first component signal and the reconstructed second component signal. The multi-component encoding method uses the inter-component prediction from one spatially corresponding part obtained by the multi-component encoding method. The third component of the current sub-portion of the current image of a component image or video. and a decoder configured to reconstruct a plurality of source component signals. In response to the transmission of an ICP signal, the device switches to the fixed single source ICP encoding mode. and wherein the multi-component image or video is fixed within each portion of the multi-component image or video. Item 1. A decoder according to item 1.

3. The transmission of the multiple source ICP signals may be performed in such a manner that the ICP mode portion (202) captures a single image, Signaling in said data stream (12) as being an image sequence or slice.

3. A decoder according to claim 2, wherein the decoder is configured to:

4. The first component (A) is luminance and the second component (B) is the first and the third component (C) is the second chroma component. A decoder according to any one of claims 1 to 3.

5. The decoder decodes the spatially corresponding first component signals (22). a current image of the multi-component image using inter-component prediction from a portion of the current image; or reconstructing said third component signal (30) of video (16); and A component signal is extracted from the spatially corresponding portion of the reconstructed second component signal (26). The third prediction in the current picture of the multi-component video using inter-component prediction. Switching between reconstructing the component signals (30) at a first sub-image granularity A decoder according to any one of claims 1 to 4, configured to:

6. The decoder decodes the spatially corresponding first component signals (22). the multi-component image or video using inter-component prediction from the corresponding part; Reconstructing a third component signal (30) in the current image of (16) and In response to transmitting (210) an explicit ICP source signal in the data stream (12), , and extracting components from spatially corresponding portions of the reconstructed second component signal (26). Current image of a multi-component image or video (16) using inter-component prediction during the reconstruction of the third component signal (30) in The method according to any one of claims 1 to 5, wherein the method is configured to switch at an image granularity level. decoder.

7. The decoder may select spatial, temporal and / or inter-view prediction modes in units of prediction blocks. By changing between modes, the spatial, temporal and / or inter-view prediction is used. Regarding the third component (C) of the multi-component image or video: configured to reconstruct the third component signal (30), the decoder comprising: configured such that the first sub-image granularity subdivides the current image in units of prediction blocks; 7. A decoder according to claim 5 or claim 6, wherein

8. The decoder generates the third component of the multi-component image or video. using spatial, temporal, and / or inter-view prediction for the Inverse transforming residual prediction by spatial, temporal, and / or inter-view prediction on a block-by-block basis. and configured to perform reconstruction of the third component signal (30) by and the decoder converts the first sub-image granularity of the current image into a transform block granularity.

7. A decoder according to claim 5 or 6, configured to subdivide Yes.

9. The decoder converts the reconstructed first component using linear prediction. a first component signal (22) and the reconstructed second component signal (26) configured to perform the inter-component prediction and to a component signal (22) and said reconstructed second component signal (26); is linearly involved in the inter-component prediction at the second sub-image granularity by weighting , in response to transmitting (212) an ICP prediction parameter signal in said data stream (12). A decoder according to any one of claims 1 to 8, configured to:

10. The decoder may select spatial, temporal and / or inter-view prediction modes in units of prediction blocks. by switching between the spatial, temporal and / or inter-view predictions. and a third component (C) of said multi-component image or video. configured to perform a reconstruction of the third component signal (30), The first sub-image granularity is set to subdivide the current image in units of prediction blocks.

10. The decoder according to claim 1, wherein the decoder is configured as follows:

11. The decoder uses spatial, temporal and / or inter-view prediction and transforms Predicting the residual by the spatial, temporal and / or inter-view prediction in units of blocks and converting the third component of the multi-component image or video into a third component by inversely transforming the to perform a reconstruction of the third component signal (30) with respect to the component (C). and the decoder is configured to:

11. The method according to claim 9, wherein the image is divided into decoder.

12. The decoder weights the data by non-uniform quantization that is asymmetric about zero. configured to extract from the transmission (212) of the ICP prediction parameter signal of the data stream. The decoder according to any one of claims 9 to 11,

13. The decoder filters the data stream with zeros belonging to a set of possible values ​​of weight. (12) extracting the weights from the transmission of the ICP prediction parameter signal (212) (220) configured such that the weighting for each block is The multi-component image signal is zero or not depending on the transmission of the parameter signal. For each block of the current image of the image or video (16), the decoder checks (222) and, if not, the data stream (12) to extract the ICP source index (210) for each block (208). 226, if possible, for each block, the ICP source Extraction of the indices is suppressed (224), and the decoder performs the following if If the weighting is not zero, then the reconstructed first component signal (22) For each block using linear prediction from the spatially corresponding block (204), and dividing the third component signal (30) according to respective non-zero weightings. or the empty space of the reconstructed second component signal (26). Each of said blocks (24) is subjected to linear prediction from the corresponding block (24). 08), in accordance with the respective non-zero weightings, To reconstruct the signal (30), the ICP source index ( The method according to any one of claims 9 to 12, wherein the method is configured to respond (230) to a request (210) from the Decoder included.

14. The decoder extracts zeros from the data stream belonging to a set of possible values ​​of the weights. (12) extracting the weights from the transmission of the ICP prediction parameter signal (212) and transmitting (212) the ICP prediction parameter signal. Whether the weighting for each block (208) satisfies a predetermined criterion is determined. of a block of the current image of said multi-component image or video, regardless of whether For each one, the decoder is checked, and if not, the data For each block from the stream, and if possible, the IC P source index (210) and extract the ICP source index for each block. and suppressing the output and setting the ICP source indicators to the respective blocks according to a predetermined standard. and weighting the reconstructed image data according to the weights for the respective blocks. the previous signal using linear prediction from the spatially corresponding block of the first component signal. to reconstruct the third component signal of each block, or the reconstructed second block weighted according to the weight for each block. Each of the above using linear prediction from spatially corresponding blocks of the component signals the respective blocks so as to reconstruct the third component signal of the block. the decoder is configured to respond to the ICP source indicator for the A decoder according to any one of claims 9 to 13.

15. The decoder first decodes the sign of the weighting and then generates a computation signal according to the sign. in the data stream by decoding its absolute value using text modeling. configured to extract the weights from the transmission (212) of the ICP prediction parameter signal. The decoder according to any one of claims 9 to 14,

16. The decoder may perform spatial, temporal and / or inter-view prediction on top of the residual prediction. applying inter-component prediction to the spatial, temporal and / or inter-view prediction; The third component of the multi-component image or video is measured using a to perform a reconstruction of the third component signal (30) for the component (C). The decoder according to any one of claims 9 to 14, configured as follows:

17. The decoder separates the first and second components of the multi-component audio signal. For each component, spatial, temporal and / or cross-view prediction within the component (34 A, 34B), and the reconstructed first component the first signal and the reconstructed second component signal are With respect to said first and second components of the audio signal, said spatial, temporal and / or or a prediction residue of inter-view prediction. A decoder according to any one of the preceding claims.

18. The decoder may further include a third component or components of the multi-component image. using intra-component spatial, temporal and / or inter-view prediction (34C); and , from the spectral domain to the spatial domain, spatial, temporal and / or Or in inter-view prediction, by inverse transforming the residual prediction (216), performing the reconstruction of the third component signal and then calculating the residual in the spatial domain; configured to apply the inter-component prediction onto the prediction or the spectral region. A decoder according to any one of claims 1 to 17, wherein

19. The decoder performs spatial, temporal and / or viewpoint prediction (34A) within a component. , 34B) to perform the reconstruction of the first and second component signals. A decoder according to any one of claims 1 to 18, configured as follows:

20. The decoder receives spatially corresponding portions of the reconstructed first component signal. (204) of the multi-component image using the inter-component prediction reconstructing the third component signal in the current image or video; and and from the spatially corresponding portions (206) of the reconstructed second component signal. the current image or the multi-component image using the inter-component prediction during reconstruction of the third component signal of the video, the reconstructed first component signal configured to switch at an image granularity; and the reconstructed second component is different from the predetermined prediction model. and using the data stream to obtain prediction parameters of a prediction model at a second sub-image granularity. In response to the meter signal, i.e., the ICP prediction parameter signal (212), the component Perform inter-component prediction to transmit explicit ICP source signals in the data stream (2 10) performing switching at the first sub-image granularity in response to the prediction performance of the prediction model; Explicit extraction from data streams using context modeling that addresses parameters The method of any one of claims 1 to 19, configured to decode transmissions of ICP source signals.

10. The decoder according to claim 9, wherein:

21. The decoder uses a prediction model controlled by gradients as the prediction parameters.

20. A decoder as claimed in claim 19, configured to use linear prediction.

22. The decoder may select the gradient for that subportion regardless of whether it is positive or negative. first, for a current sub-portion of a current image of said multi-component image or video, Check (229) and perform the context modeling in response to the check.

22. A decoder according to claim 19 or claim 21, configured so that

23. The decoder determines whether the gradient for that sub-portion is within a predetermined interval. Check for the current sub-portion of the current picture in a component image or video and performing context modeling in response to said checking. A decoder according to claim 19 or claim 22.

24. The decoder may include a predetermined number of the current image of the multi-component image or video. and extracting first and second predicted parameters from said data stream (12) for the selected subportion. and obtaining a reconstructed meter using a predetermined prediction model and the first prediction parameters. and performing inter-component prediction from the first component signal (22) to obtain the predetermined A reconstructed second component using the estimated prediction model and the second prediction parameters. The inter-component prediction is performed from the input signal (26) to obtain a linearly reconstructed first The inter-component prediction from the component signal and the reconstructed second component and inter-component prediction from the component signal. A decoder according to any one of claims 1 to 23.

25. The decoder outputs the reconstructed third component signal at a third sub-image granularity. and the reconstructed second component signal.

24. The method according to claim 1, wherein the method responds to a transmission (248) of a swap signal by a Decoder included.

26. IC for the third component signal (30) of the data stream (12). In response to transmitting (212) P prediction parameter signals, a first iteration of the prediction model is performed at sub-image granularity. By switching between three component prediction parameters, a predetermined prediction model can be used. the reconstructed first component signal (22) and the reconstructed second component signal (23) a decoder for performing the inter-component prediction from two component signals (26); The coda is composed, and deriving the inter-component prediction from the reconstructed first component signal (22); The second component (B) or video component of the multi-component image is used. performing a reconstruction of the second component signal (26) with respect to the digital signal; ICP prediction parameters for the second component signal of the data stream (12). Component signal prediction parameters of the prediction model at sub-image granularity in response to transmission of the signal. The reconstructed first prediction model is used by switching A decoder (20) for performing the inter-component prediction from the component signals (22). Da is constructed, and The prediction parameters of the second component and the third component are predetermined. If the difference is more than the specified limit, and if it is not due to location, For each location from the data stream, an ICP source index (21) is calculated for that location. 0), and if yes, suppress the extraction of the ICP Source Indicator (210), The ICP source index (210) is set to a predetermined standard at each location, and then the data The coder generates an ICP source index (210) for each location in each third component. the reconstructed first component is weighted by a component prediction parameter, Each case is calculated using linear prediction from the spatially corresponding position of the component signal. and an ICP source indicator (210) for reconstructing the third component signal. or (each third component predictive parameter the spatially corresponding second component signals are weighted by the Reconstructing the third component signal at each location using linear prediction from the location. A decoder according to any preceding claim, adapted to construct

27. Regarding the third component (C) of the multi-component image or video: When reconstructing the third component signal (30), A residual signal for the component-to-component signal is extracted from the data stream, thereby A decoder according to any one of claims 1 to 26, adapted to correct the prediction. Yes.

28. Sampling the scene for spatially distinct components and creating multi-component 1. A method for decoding an image or video (16), comprising: The method comprises: The multi-component image or video ( Reconstructing the first component signal (22) in terms of the first component (A) of The construction process, The multi-component image or video ( Reconstructing the second component signal (26) in terms of the second component (B) of The process of building The reconstructed first component signal (22) and the reconstructed second component signal (24). The multi-component signal (26) is obtained by using inter-component prediction. a third component (C) relating to the first image or the third component (C) of said video (16); reconstructing a component signal (30).

29. A first input of a multi-component image or video (16) into a data stream (12). encoding a first component signal (22) with respect to a component (A); The data stream (12) includes the multi-component image or the video (1 6) encoding the second component signal (26) with respect to the second component (B) of To do, The encoded first component signal (22) and the encoded second component signal (23) The multi-component signal (26) is obtained by using inter-component prediction. A third component (C) relating to the image or the third component of said video (16) By encoding the event signal (30), Sampling the scene for spatially distinct components and an encoder configured to encode the component image or the video (16).

30. Sampling the scene for spatially distinct components and creating multi-component 1. A method for encoding an image or video (16), comprising: The data stream (12) includes a first component of a multi-component image or video (16). encoding a first component signal (22) with respect to one component (A); 、 The data stream (12) includes the multi-component image or the video (1 6) encoding the second component signal (26) with respect to the second component (B) of and The encoded first component signal (22) and the encoded second component signal (23) The multi-component signal (26) is obtained by using inter-component prediction. A third component (C) relating to the image or the third component of said video (16) encoding a signal (30).

31. A computer program is a program that, when run on a computer, 31. The method of claim 28 or claim 30, wherein the gram code is

Images