228 results about "Lossless coding" patented technology

An apparatus and method for image data compression performs a modified zero-tree coding on a range of image bit plane values from the largest to a defined smaller value, and a vector quantizer codes the remaining values and lossless coding is performed on the results of the two coding steps. The defined smaller value can be adjusted iteratively to meet a preselected compressed image size criterion or to meet a predefined level of image quality, as determined by any suitable metric. If the image to be compressed is in RGB color space, the apparatus converts the RGB image to a less redundant color space before commencing further processing.

A video coding algorithm supports both lossy and lossless coding of video while maintaining high color fidelity and coding efficiency using an in-loop, reversible color transform. Accordingly, a method is provided to encode video data and decode the generated bitstream. The method includes generating a prediction-error signal by performing intra/inter-frame prediction on a plurality of video frames; generating a color-transformed, prediction-error signal by performing a reversible color-space transform on the prediction-error signal; and forming a bitstream based on the color-transformed prediction-error signal. The method may further include generating a color-space transformed error residual based on a bitstream; generating an error residual by performing a reversible color-space transform on the color-space transformed error residual; and generating a video frame based on the error residual.

A time-discrete audio signal is processed to provide a quantization block with quantized spectral values. Furthermore, an integer spectral representation is generated from the time-discrete audio signal using an integer transform algorithm. The quantization block having been generated using a psychoacoustic model is inversely quantized and rounded to then form a difference between the integer spectral values and the inversely quantized rounded spectral values. The quantization block alone provides a lossy psychoacoustically coded/decoded audio signal after the decoding, whereas the quantization block, together with the combination block, provides a lossless or almost lossless coded and again decoded audio signal in the decoding. By generating the differential signal in the frequency domain, a simpler coder/decoder structure results.

In a method of lossless processing of an integer value signal in a prediction filter which includes a quantiser, a numerator of the prediction filter is implemented prior to the quantiser and a denominator of the prediction filter is implemented recursively around the quantiser to reduce the peak data rate of an output signal. In the lossless processor, at each sample instant, an input to the quantiser is jointly responsive to a first sample value of a signal input to the prediction filter, a second sample value of a signal input to the prediction filter at a previous sample instant, and an output value of the quantiser at a previous sample incident. In a preferred embodiment, the prediction filter includes noise shaping for affecting the output of the quantiser.

A method for coding a video sequence is provided that includes encoding a portion of a picture in the video sequence in lossless coding mode, and signaling a lossless coding indicator in a compressed bit stream, wherein the lossless coding indicator corresponds to the portion of a picture and indicates whether or not the portion of the picture is losslessly coded. A method for decoding a compressed video bit stream is provided that includes determining that lossless coding mode is enabled, decoding a lossless coding indicator from the compressed video bit stream, wherein the lossless coding indicator corresponds to a portion of a picture in the compressed video bit stream and indicates whether or not the portion of the picture is losslessly coded, and decoding the portion of the picture in lossless coding mode when the lossless coding indicator indicates the portion of the picture is losslessly coded.

A lossless audio coding and/or decoding method and apparatus are provided. The coding method includes: mapping the audio signal in the frequency domain having an integer value into a bit-plane signal with respect to the frequency; obtaining a most significant bit and a Golomb parameter for each bit-plane; selecting a binary sample on a bit-plane to be coded in the order from the most significant bit to the least significant bit and from a lower frequency component to a higher frequency component; calculating the context of the selected binary sample by using significances of already coded bit-planes for each of a plurality of frequency lines existing in the vicinity of a frequency line to which the selected binary sample belongs; selecting a probability model by using the obtained Golomb parameter and the calculated contexts; and lossless-coding the binary sample by using the selected probability model. According to the method and apparatus, a compression ratio better than that of the bit-plane Golomb code (BPGC) is provided through context-based coding method having optimal performance.

The disclosure relates to encoding and decoding of digital data, and in particular to lossless arithmetic encoding and decoding of digital data representing audio, image or video data. A probability density function used for lossless arithmetic encoding of digital data is controlled by employing one or more parameters that changes over the set of data to be encoded. A parametric model in the form of an envelope function describes the spread of quantization indices derived from the data in a transform domain. By transmitting the one or more parameters together with the arithmetically encoded data, a receiving decoder may decode the data by exploiting the same parametric model as used by the encoder.

When processing a signal having a sequence of discrete values, wherein there is a first frequency range, in which the signal has a high energy, and wherein there is a second frequency range, in which the signal has a low energy, the sequence of discrete values is first manipulated to obtain a sequence of manipulated values, so that at least one of the manipulated values is non-integer. Then the sequence of manipulated values is rounded to obtain a sequence of manipulated values. The rounding is formed to effect a spectral shaping of a generated rounding error so that a spectrally shaped rounding error has a higher energy in the first frequency range than in the second frequency range. By spectrally shaping the rounding error so that the rounding error does not have any energy either in the storage areas where there is no signal energy, an especially efficient coding is obtained particularly in connection with a lossless coding context.

According to this invention, while the encoding efficiency of image data (e.g., a natural image) substantially maintains the conventional one, an image (e.g., a CG image or text document) having a small number of appearance colors is losslessly encoded at higher compression ratio. For this purpose, pixel data are input in the raster order and temporarily stored in a buffer. Pixel data at positions having undergone encoding are stored. A neighborhood matching determination unit generates first information representing whether a pixel having the same color as that of the pixel of interest exists in neighboring pixels a, b, and c, and second information for specifying whether a pixel having the same color as that of the pixel of interest exists, and if the pixel having the same color exists, specifying the neighboring pixel. A pixel matching detection unit counts the number of colors contained in the neighboring pixels a, b, and c, and generates information representing whether the number of colors is two or less, or three or less. On the basis of the first information and second information, a code generation unit outputs one or both of encoded data from a matched-pixel position encoding unit and prediction error encoding unit.

In this invention, image data expressed by one component is encoded at a high speed by using a color image lossless encoder. To do this, a color conversion unit converts color image data read by a document reading unit into C, M, Y, and K data. In a color reading mode, a switching unit directly outputs the C, M, Y, and K data to an encoding unit. If the reading mode is a monochrome reading mode, the switching unit neglects the C, M, and Y components of the C, M, Y, and K data. Every time four K components are input, the switching unit supplies the four K components to the encoding unit as pseudo data of C, M, Y, and K color components. The encoding unit lossless-encodes the received C, M, Y, and K component data.

A configuration for encoding and decoding the data is disclosed herein. A server retrieves webpage content to filter and extract text and image data. The text data is encoded using a lossless encoder, whereas the image data is downsampled to a lower resolution and encoded using a lossy encoder. The encoded text and image data is transmitted over a network. Once the encoded data is received on the client device, the text and image data is decoded using an inverse encoding algorithm and resized at a resolution appropriate to the native resolution of the display device.

A lossless encoder and decoder are provided for transmitting a multichannel signal on a medium such as DVD-Audio. The encoder accepts additionally a downmix specification and splits the encoded stream into two substreams, such that a two-channel decoder of meagre computational power can implement the downmix specification by decoding one substream, while a multichannel decoder can decode the original multichannel signal losslessly using both substreams. Further features provide for efficient implementation on 24-bit processors, for confirmation of lossless reproduction to the user, and for benign behaviour in the case of downmix specifications that result in overload. The principle is also extended to mixed-rate signals, where for example some input channels are sampled at 48 kHz and some are sampled at 96 kHz

A high degree of compression can be achieved in audio and image coding systems by using a multiple-stage lossless encoding process having low computational cost that does not require high-accuracy pre-defined probability distribution functions of the information to be compressed. The multiple-stage encoding process classifies the signal components to be compressed into one of several classifications according to signal component value. Signal components placed into higher-level classifications are represented by tokens in the lower-level classifications. Each stage of the encoding process forms groups of signal components and tokens and applies a multi-dimensional encoding process to the groups. The dimension of the coding process is equal to the size of the group to which it is applied, and is chosen to balance computational requirements of the encoding process against compression performance.

Methods and systems for encoding, transmitting and decoding digital images by rate-distortion adaptive zerotree-based residual vector quantization are disclosed. A method of the invention includes receiving a digital image, transforming the digital image into the wavelet domain generating a pyramid hierarchy, losslessly encoding a top LL subband from the pyramid hierarchy, encoding other subbands by vector quantization based on a zerotree insignificance prediction, generating an encoded image from the lossless encoding and vector quantization encoding, transmitting the encoded image along a communications channel, receiving the encoded image transmitted along the communications channel, reconstructing a zerotree from the encoded image, vector quantization decoding subbands from the encoded image other than a top LL subband, losslessly decoding the top LL subband from the encoded image, reverse wavelet transforming the top LL subband and the vector quantization decoded subbands and outputting a decoded image.

The present invention relate to methods and codecs for image and video compression. Embodiments of the present invention include a novel shape-adaptive model-based codec (SAM) that supports binary shapes as well as matte and soft segmentation image compression by decomposing input shapes into deterministic and stochastic components for flexible lossy and lossless coding. The present invention can provide inter/intra prediction and flexibly adapts between lossy and lossless modes with various parameters for compression quality control. The compression module can also be adapted with numerous other compression techniques.

The invention relates to digital image compression technology, in particular to a method for encoding and decoding Bayer patter images, and aims to solve the problem of the difficult establishment of good balance between compression ratio, quality and complexity of restructured color images in the prior method which compresses Bayer pattern image data directly. The invention uses LOCO-I technology to perform lossless encoding for a green component; and through estimation of the green component on the site of a red-blue component by a gradient interpolation method, a color difference signal between the small-wave low-frequency subband of the red-blue component and the low-frequency subband of the estimated green component can be acquired, and can undergo lossless or nearly lossless compression by the LOCO-I technology. At the decoding end, the lossless green component should be obtained firstly, then the green component on the site of the red-blue component is estimated through an process identical to the encoding process; the small-wave high-frequency subband of the estimated green component can replace the corresponding small-wave high-frequency subband of the red-blue component, and the rest part is a reverse process of encoding. The method is characterized by high efficiency and low complexity.

Lossless and lossy codes are combined for data compression. In one embodiment, the most significant bits of each value are losslessly coded along with a lossy version of the original data. Upon decompression, the lossless reduced-precision values establish absolute bounds for the lossy code. Another embodiment losslessly codes the leading bits while trailing bits undergo lossy coding. Upon decompression, the two codes are summed. The method preserves edges and other sharp transitions for superior lossy compression. Additionally, the method enables description-length inference using noisy data.

Provided is an encoding device (1) including: a pitch contour analysis unit (101) which detects information, a dynamic time-warping unit (102) which generates, based on the information, pitch change ratios (Tw_ratio in FIG. 18) within a range (86) including a range (86a) of the pitch change ratios corresponding to absolute pitch differences of 42 cents or larger; a first lossless coding unit (103) which codes the generated pitch parameters (102x); a time-warping unit (104) which shifts a pitch of a signal according to the information; and a second encoding unit which codes a signal (104x) obtained by the shifting.