39 results about "Discrete cosine transform" patented technology

The invention relates to the technical field of voice processing, can be applied to service system platforms of medical health, financial science and technology, communication and the like, and discloses an audio compression and reconstruction method, device, equipment and medium. Residual vector quantization and inverse quantization are carried out to generate basic spectrum features; and compensating a high-frequency component by adopting a spectrum expansion network, predicting a time domain error in combination with a long-short-term memory network, generating a time domain residual compensation signal, and superposing the time domain residual compensation signal with the reconstructed time domain audio signal to obtain a target audio signal. Through residual vector quantization and neural network modeling, the audio reconstruction quality under low-bit-rate compression is improved, spectrum detail reservation and time domain error compensation are optimized, meanwhile, the calculation complexity is reduced, and the method is suitable for high-sampling-rate and resource-limited scenes.

The invention discloses a 3D human body posture estimation method based on a diffusion model. According to the method, firstly, a continuous human body dynamic video is split into RGB images, two-dimensional coordinate information, embedded time steps and positions of all joint points of a human body are extracted from the RGB images through a 2D posture detector, then predicted 3D postures are output through a diffusion model, and low-frequency key information is reserved and high-frequency noise is filtered in combination with discrete cosine transform (DCT), so that the 3D postures are obtained. And the calculation complexity is greatly reduced. And based on a multi-hypothesis aggregation strategy of confidence and consistency evaluation, weighted fusion is performed on the predicted 3D postures, so that the precision and robustness of posture estimation are improved. The performance of the model in a dynamic scene is further enhanced by a time step embedding mechanism and time consistency scoring, so that the model adapts to a complex motion environment and a shielding condition. The method is low in computing resource demand, is suitable for being deployed on resource-constrained equipment in the fields of human-computer interaction, virtual reality, motion analysis, medical rehabilitation and the like, and has a wide application prospect.

The invention discloses an adaptive blocking compressed sensing image super-resolution reconstruction method and system. The method comprises the following steps: acquiring a low-resolution image and carrying out adaptive blocking on the low-resolution image; establishing a sparse representation model of the high-resolution image by using a discrete cosine transform basis; establishing an observation dimension reduction model by using the binary block diagonal matrix to obtain a relationship between a high-resolution image and a low-resolution image; performing compressed sensing super-resolution reconstruction solution on the low-resolution sub-block images by using a weighted iterative least square algorithm to generate high-resolution image blocks, and performing constraint by using Shearlet transformation and dual-scale total variation regularization in the reconstruction process; and splicing the generated high-resolution image blocks according to the position indexes to obtain a complete high-resolution image meeting the requirements. According to the method, the problems of unreasonable blocking caused by single blocking basis and limited reconstruction effect caused by insufficient consideration of prior information in the existing method are solved.

The invention discloses a wavelet domain audio zero watermark algorithm based on dual-tree complex wavelet transform (DTCWT), variational mode decomposition (VMD) and discrete cosine transform (DCT). Firstly, encryption protection is carried out on a watermark image, then framing is carried out on an original audio signal, dual-tree complex wavelet transform (DTCWT) and variational mode decomposition (VMD) are carried out on each frame, a first IMF is taken to carry out DCT, and a feature vector is obtained. And finally, carrying out XOR operation on the polarity feature vector and the scrambled watermark to obtain a zero watermark key. Experiments show that the method can effectively resist conventional attacks, and especially has good robustness to noise attacks.

The invention relates to the field of hybrid coding of video engines, and provides a hybrid coding processing method, system and equipment based on a video engine, which comprises the step of intelligently switching an H.265 inter-frame predictive coding mode and an MJPEG (Multijoint Joint Photographic Experts Group) intra-frame compression coding mode by dynamically monitoring the proportion of a motion area in a video picture. When a scene is static, discrete cosine transform is adopted to compress space redundancy, motion vector compensation is started to eliminate time redundancy when motion is violent, and meanwhile, key frames are doubly screened by using pixel difference analysis and a perceptual hash algorithm, and repeated frames of visual redundancy are eliminated. And finally, space-time association is established for the optimized double-code-stream data through a timestamp index system, and efficient storage and accurate reconstruction of the mixed code stream are realized. The problems that the coding efficiency is low, no self-adaptive coding mode exists, redundant frames are not optimized, and code stream management is insufficient are solved.

The invention relates to a multi-room audio playing method and system, electronic equipment and a storage medium. The method comprises the following steps: acquiring layout information of a current playing audio space; according to the layout information, audio devices of all rooms in an audio playing space are combined into an initial playing framework; acquiring a connection relationship of each audio device in the initial playing architecture; and updating the initial playing architecture based on the connection relationship to obtain an audio playing architecture, thereby realizing multi-room audio playing through the audio playing architecture. A C / S framework is adopted, frequency domain information loss possibly occurring in the discrete cosine transform and auditory masking effect processing process is avoided, it is ensured that original sound wave harmonic details are completely reserved, a server side adds a globally unique timestamp for each frame of audio data by obtaining a microsecond-level system clock, and therefore the accuracy of audio data processing is improved. And the coded data block is transmitted to the connected client through the TCP protocol, so that the problem that the sound quality is possibly reduced during synchronous playing of a multi-room system is avoided.

The invention discloses a flexible touch glove pressure array signal completion method based on compressed sensing. According to the method, an existing flexible touch glove is used for conducting signal collection on the external environment to obtain a pressure distribution diagram; converting the analog signal into a digital signal through analog-to-digital conversion and outputting the digital signal; the existing pressure image signal is sampled through a sampling link to obtain a sampled image, and in the process, the image size can be compressed, and meanwhile, part of noise can be eliminated; and performing two-dimensional discrete cosine transform on the sampling image signal through a two-dimensional transform link to obtain an initial reconstruction image signal. And then, a compressed sensing network is used for carrying out signal processing on the initial reconstruction image signal to obtain a final reconstruction image signal, and the process can obviously improve the imaging quality of the tactile acquisition image. The method can be used in the fields of object recognition, industrial automatic detection and the like.

This disclosure provides methods, components, devices and systems for multirate audio mixing. Some aspects more specifically relate to mixing audio streams with different sample rates. In some examples, an audio source device may convert audio streams with different sample rates to the frequency domain using a modified discrete cosine transform (MDCT), and the audio source device may mix the audio streams with different sample rates in the frequency domain. The audio source device may apply a pre-emphasis filter after mixing the audio streams in the frequency domain. An audio stream with a higher sample rate may be down-sampled by dropping frequency bins after converting the audio stream to the frequency domain. Additionally, or alternatively, an audio stream with a lower sample rate may be up-sampled by padding frequency bins of the frequency domain-converted audio stream.

A method for decoding a video includes determining, from multiple sets of multiple transform selection candidates, one set of multiple transform selection candidates based on at least one of a number of non-zero coefficients in a current block and a position of a last non-zero coefficient in the current block. The method for decoding the video also includes selecting one inverse transform method based on the one set of multiple transform selection candidates. The method for decoding the video further includes generating a residual block of the current block by performing the one inverse transform method on coefficients of the current block, where the multiple sets of multiple transform selection candidates have one or more candidates that correspond to a non-Discrete Cosine Transform 2 (non-DCT 2) inverse transform method.

The application discloses a kind of high-efficiency Gaussian splashing reconstruction method and device for dynamic endoscope scene in the technical field of medical image processing, comprising: the endoscope video sequence obtained is preprocessed, and initial Gaussian point cloud is generated;The motion trajectory of each Gaussian point in initial Gaussian point cloud is modeled using Gaussian point cloud morphing model based on discrete cosine transform, and dynamic Gaussian scene is generated;The dynamic and static attributes of Gaussian point cloud morphing model based on discrete cosine transform are compressed and stored using residual-aware hybrid precision quantization strategy;Dynamic Gaussian scene is rendered using hardware-aware dense inference strategy, and three-dimensional reconstruction image of endoscope video is generated in real time.The application can effectively improve the expression efficiency of endoscope scene dynamic modeling, while reducing storage / deployment overhead.

The invention discloses an editing tool traceability method for multi-tool editing images, and the method comprises the steps: extracting frequency domain block-level features through sliding window discrete cosine transform based on a dual-domain block feature enhancement mode of a spatial domain and a frequency domain for a to-be-traced image data set, and combining the spatial domain block-level features to obtain a to-be-traced image data set; realizing double-domain feature fusion by adopting a cross-attention mechanism, and outputting fusion features; based on a training data sampling strategy of error feedback, a training sample is divided into a plurality of subsets according to the number of editing steps, the sampling weight is dynamically adjusted based on error feedback of each subset, and model training is optimized; and inputting the fusion features into the optimized model to realize traceability of each editing tool. According to the method provided by the invention, one-time accurate identification of all the editing participating tools in the multi-tool editing image can be realized.

The present application discloses a speech filtering method, device, storage medium and equipment, which belongs to the field of speech coding and decoding technology. The method mainly includes: encoding the speech signal according to a standard Bluetooth encoder without a post-filtering module, and decoding the encoded speech signal to a transform domain noise shaping decoding module according to a standard decoder without a post-filtering module to obtain speech spectrum coefficients; inputting the speech spectrum coefficients into a pre-trained neural network model to obtain target spectrum coefficients corresponding to the speech spectrum coefficients; and according to the remaining decoding steps of the standard decoder without a post-filtering module, inputting the target spectrum coefficients into the low-latency improved inverse discrete cosine transform module of the standard decoder to obtain the target speech signal corresponding to the target spectrum coefficients. The present application omits the complex post-filtering operation in the Bluetooth encoding process, and only uses the pre-trained neural network model for filtering in the Bluetooth decoding process, so that it achieves a sound quality close to that of standard decoding.

The invention relates to a self-adaptive robust video watermarking method based on H.264AVC video coding. The self-adaptive robust video watermarking method comprises the steps of preprocessing, watermark embedding and extracting. The method comprises the following steps: preprocessing: graying an image, carrying out integer discrete cosine transform and quantization processing on a gray value, then carrying out Z-shaped coefficient scanning, then carrying out data formula transformation and 4-bit unsigned binary coding conversion, and finally introducing an error correction coding link for improving the watermark data recovery capability. When a watermark is embedded, deterministic mapping from a macro block group to a bit is established in a key frame, and the same information is embedded in a distributed manner at different time points. During watermark extraction, a judgment method based on bit-level majority statistics is introduced so as to perform fusion processing on extraction results of the same watermark line in a plurality of key frames. According to the method, the overall performance of the watermarking system in the aspects of synchronism, robustness and invisibility can be improved.

The invention discloses a voice noise reduction method and device in combination with non-negative matrix factorization and time-frequency masking and a storage medium, and belongs to the technical field of Bluetooth audios, and the method comprises the steps: inputting monaural voice PCM data, and executing low-delay improved discrete cosine transform to obtain an MDCT spectral coefficient; calculating sub-band energy according to the MDCT spectrum coefficient, and constructing a noisy voice amplitude spectrum observation matrix; performing non-negative matrix factorization on the noisy voice amplitude spectrum observation matrix, and calculating an NMF amplitude spectrum gain; performing feature extraction according to the sub-band energy, and calculating an NN amplitude spectrum gain through a pre-trained deep neural network; fusing the NMF amplitude spectrum gain and the NN amplitude spectrum gain, and outputting a noise reduction gain; obtaining a noise reduction spectral coefficient according to the noise reduction gain and the MDCT spectral coefficient; and according to the noise reduction spectrum coefficient, continuing to execute the coding process, and outputting a noise reduction voice code stream. According to the invention, based on the MDCT spectral coefficient, voice noise reduction is realized by combining non-negative matrix factorization and time-frequency masking, and the tone quality is ensured.

The present application discloses a method, apparatus, device, and medium for extracting video watermarks based on a quick response code, relating to the field of image processing technology. The method comprises: obtaining a first scene change frame and a quick response code matrix of a first video, processing the above contents separately to obtain an encrypted quick response code matrix and multiple image blocks of different sizes; performing a discrete cosine transform on the luminance component of the first scene change frame, combining the encrypted quick response code matrix to obtain DC coefficients and AC coefficients; then performing an inverse discrete cosine transform on the multiple image blocks of different sizes to embed watermark information and obtain a first video with a watermark; processing the first video with a watermark to obtain a target estimated value of the encrypted quick response code matrix; decrypting and decoding the target estimated value in sequence to obtain target watermark information, thereby extracting the watermark information. The method can dynamically adjust the size of the embedded watermark, improve extraction efficiency, and enhance the security of the watermark.

The invention discloses a forgery positioning method based on attention enhancement and adaptive frequency selection, and belongs to the technical field of image forgery detection. The invention aims to solve the problem of poor positioning precision and robustness caused by inaccurate feature capture of a forged area and insufficient utilization of multi-scale and frequency information in the existing forged positioning technology. The scheme comprises the following steps: extracting multi-scale spatial features of an input image through an encoder; channel and space attention weighting is carried out on the multi-scale features by using an attention enhancement module so as to enhance and counterfeit related features; carrying out discrete cosine transform and adaptive weight learning on the enhanced features by adopting an adaptive frequency selection module, screening effective frequency components and carrying out cross-domain fusion; and finally, generating a positioning mask of the forged region based on the fusion features. The method can effectively improve the positioning accuracy of the forged area in the image and the robustness in a complex scene, and is suitable for digital media evidence obtaining and content security auditing.

The invention discloses an audio understanding method and system, electronic equipment and a storage medium, and the method comprises the steps: obtaining each coding unit of each audio clip of a target audio, and carrying out the compression through discrete cosine transform based on the information entropy of each coding unit, and obtaining a compressed coding unit; polling each audio clip, and calculating the acoustic significance membership degree of each compressed coding unit and the time sequence correlation membership degree of each current fusion coding unit of the previous audio clip; calculating the contribution weight of each compression coding unit and the contribution weight of each current fusion coding unit to the compression coding unit by using the membership degree of each compression coding unit; respectively utilizing the contribution weight corresponding to each compression coding unit to carry out weighted summation on the compression coding unit and each current fusion coding unit to obtain each fusion coding unit of the current audio clip, inputting the fusion coding units into a large language model, and outputting an understanding analysis result; and fusing the understanding analysis results into a result of the target audio.

The invention provides an image compression system and method. The method includes acquiring an image frame and dividing it into a set of image blocks. Then obtaining a preliminary quantitative configuration file; each image block is subjected to a discrete cosine transform (DCT) to create a frequency dependent image profile, which is then quantized using a preliminary quantization profile and compressed using at least one compression encoding algorithm. And comparing the size of the compressed image frame with a target size range, and updating the preliminary quantitative configuration file according to a comparison result. In addition, the method further comprises the step of dynamically adjusting the target size range according to the environment or network condition of the system, so that the real-time adaptability and efficiency of processing the dynamic environment and the complex scene are improved.

The application provides an image denoising method based on frequency space joint guided dynamic kernel generation network, which comprises the following steps: inputting a noisy image into an initial convolution layer to obtain a shallow feature representation; adopting an encoder to perform hierarchical down-sampling and context extraction, and recovering spatial details through a jump connection in a decoder; adopting a fixed two-dimensional discrete cosine transform filter bank to perform low-frequency, medium-frequency and high-frequency decomposition on the input feature to construct a frequency prior; fusing spatial context information, channel interaction information and the frequency prior to generate a dynamic convolution kernel; performing frequency space joint guided dynamic feature extraction on multiple receptive field scales; interacting and fusing channel, height and width dimension information through a multi-dimensional adaptive fusion mechanism; finally, completing detail recovery in the decoding stage and outputting a denoised image; and the application alleviates the confusion between high-frequency texture and noise residual, and improves the detail preservation capability and denoising robustness in complex texture, strong noise and scale change scenes.

The application provides an image processing and rock mineral identification method based on high-frequency filtering and mineral component attention, and belongs to the technical field of rock mineral identification. The method is started from the perspective of the frequency domain, the discrete cosine transform is introduced into the CNN architecture, high-frequency features are explicitly enhanced, high-frequency information is directly extracted and enhanced, and the influence of the smoothing effect of the CNN in layer-by-layer transmission on the detail information can be effectively relieved; the multiple attention mechanisms in the channel dimension and the spatial dimension enable the model to automatically determine which features are more important according to the current input rock mineral image, and realize efficient adaptive optimization and extraction of complex texture structures. Experimental results show that the strategy of explicitly enhancing high frequencies in the frequency domain and the spatial-channel double attention collaborative work makes the model show higher identification accuracy when facing actual rock mineral images with complex composition, variable structure and strong background interference.

This application relates to the field of hybrid coding in video engines, providing a hybrid coding processing method, system, and device based on a video engine. This includes intelligently switching between H.265 inter-frame predictive coding and MJPEG intra-frame compression coding modes by dynamically monitoring the proportion of moving areas in the video frame. When the scene is static, discrete cosine transform is used to compress spatial redundancy; when there is rapid motion, motion vector compensation is used to eliminate temporal redundancy. Simultaneously, pixel difference analysis and perceptual hashing algorithms are used to dual-filter keyframes, eliminating visually redundant duplicate frames. Finally, a timestamp indexing system is used to establish spatiotemporal correlation between the optimized dual-stream data, achieving efficient storage and accurate reconstruction of the hybrid bitstream. This solves the problems of low coding efficiency, lack of adaptive coding modes, unoptimized redundant frames, and insufficient bitstream management.

The application provides a digital audio embedding and detecting method, which comprises the following steps: generating watermark information according to time and watermark load equipment coding; then performing frame processing on the audio to be embedded with the watermark, and performing two-stage wavelet decomposition; embedding a synchronization code in the first half of the low-frequency wavelet coefficient, and performing discrete cosine transform and singular value decomposition processing on the second half of the low-frequency wavelet coefficient to embed the watermark information; finally, in the watermark detecting stage, firstly, the audio subjected to attack in the current sliding window is subjected to two-stage wavelet decomposition through a sliding window method, whether the current sliding window contains the synchronization code is confirmed, the position of the synchronization code is determined, frame synchronization is realized, and then the second half of the audio frame subjected to attack and frame synchronization is processed to extract the watermark information. The synchronization code and the watermark information are embedded in the audio at the same time, the problem that the embedding position of the watermark in the detecting stage is difficult to position and the problem that the watermark is difficult to resist synchronous attacks such as cutting are solved, and the watermark detecting efficiency and accuracy are improved.

The invention discloses a video recompression evidence obtaining method for intra-frame and inter-frame prediction information fusion. The method comprises the following steps: extracting primary code stream characteristics of a prediction frame, constructing a prediction frame matrix and a motion vector, determining a prediction frame attribute mark, determining a prediction frame compression trace image, determining a compression ratio of an intra-frame compression trace image, determining a Fourier transform coefficient of the intra-frame compression trace image, and determining an autocorrelation coefficient of an inter-frame compression trace image. Determining a two-dimensional discrete cosine transform value of the inter-frame compression trace image, determining a high-level code stream feature matrix, and determining a re-compression evidence obtaining result. According to the method, the problem that only intra-frame prediction information is considered and inter-frame prediction information is not considered in the prior art is solved, and compared with an existing video recompression evidence obtaining method, the evidence obtaining accuracy of the method is higher than 80%. According to the method disclosed by the invention, the complexity of evidence obtaining time is reduced, the evidence obtaining precision is obviously improved, the improvement is relatively obvious under a high code rate, and the method can be applied to the technical field of video recompression evidence obtaining.

Techniques for transcoding textures are described that include computing a plurality of endpoint colors of a macroblock. In a first technique, a forward discrete cosine transform (DCT) is applied (406) to a macroblock or portion thereof and used to represent the corresponding portion. In a second technique, a mean value of the endpoint colors and a difference between the endpoint colors are calculated (206), where the mean value and the difference establish (208) a projection vector in a color space. Means and differences are compressed (210), and per-pixel distances along the projection vector are calculated (212) and used together with corresponding mean and differences to represent macroblocks.

Systems, methods, and means for video encoding / decoding are disclosed for the use of Low Frequency Inseparable Transform (LFNST) and Non-Discrete Cosine Transform 2 (DCT2) master transforms. In the examples, a video decoding device can determine whether to disable the Inseparable Master Transform (NSPT) for the current block. If NSPT is disabled for the current block, the video decoding device can determine to use LFNST for the current block. If LFNST is used, the video decoding device can decode the current block based on Multiple Transform Selection (MTS). In the examples, a video encoding device can disable NSPT for the current block. A video encoding device can enable LFNST for the current block. A video encoding device can encode the current block based on MTS.

For compressing synthetic aperture radar (SAR) images, preprocessing operations are performed on an input SAR image. A discrete cosine transform is performed on the image, and multiple subbands are created, where each subband represents a particular range of frequencies. The subbands are organized into multiple groups, where the multiple groups comprise a first low frequency group, a second low frequency group, and a high frequency group. A latent space representation is generated corresponding to each of the multiple groups of subbands. Compression is performed on one or more of the subbands, thereby creating a compressed bitstream, wherein the compressed bitstream is a compressed version of the input SAR image.

The disclosure herein provides for methods, apparatuses and non-transitory computer-readable storage media for video decoding and encoding. In example, a method for video decoding, including: obtaining, by a decoder, enabling flags at a first level for at least one mode of intra and inter coding modes, the enabling flags indicating whether Fractional Discrete Cosine Transform (FRDCT) is enabled for the at least one mode; and in response to the FRDCT being enabled at the first level, obtaining, by the decoder, a second flag at a coding unit (CU) level to indicate whether a FRDCT transform is applied to a CU.

The present invention proposes a lidar position recognition method using binary fingerprints to match loopback frames, encodes different heights of point clouds into global descriptors, and extracts row vectors containing the farthest distance for descriptor alignment. The main information of the global descriptors is concentrated by performing two-dimensional discrete cosine transform on the global descriptors, and then the low-frequency part values of the image are intercepted and then a binary image fingerprint with a small size is generated. The Hamming distance between two fingerprints is used to evaluate the similarity of the scenes. The present invention has a high recognition rate for loopbacks and good robustness for sparse point clouds.

To provide methods, programs and systems for fixed bitrate intraframe compression of video based on 2D discrete cosine transform (DCT) to control a target code amount, on the basis of the visual quality of final decompressed imagery.SOLUTION: A method involves assigning an initial bit budget per macroblock of a given video frame, resulting in degrees of compression, i.e., quantization scale factors, that vary among the macroblocks according to the complexity of the macroblocks. The scale factors are then adjusted while maintaining the overall frame bit budget to reduce the visibility of artifacts in the decompressed frame. The adjustments may include increasing scale factors for simple macroblocks, and reducing scale factors for complex blocks. This can reduce the visibility of compression-related artifacts both in complex and simple portions of the frame.SELECTED DRAWING: Figure 2

The present invention discloses a method and device for detecting facial images generated by a local GAN ​​using adaptive frequency perception, comprising: obtaining a facial image; detecting the facial image using a trained local GAN-generated facial image detection model to obtain a local GAN-generated facial image detection result; the local GAN-generated facial image detection model includes an adaptive frequency perception module and a detection network; wherein the adaptive frequency perception module includes a two-dimensional discrete cosine transform submodule, a learnable filter bank, and a two-dimensional inverse discrete cosine transform submodule arranged in sequence, the learnable filter bank including a high-pass filter and a learnable filter; and the detection network is obtained by deleting the fourth to eleventh residual blocks in an Xception network and adding an ECA attention module to the first to third and twelfth residual blocks. The present invention can accurately detect facial images generated by local GAN ​​and has good generalization and robustness.