9results about How to "Reduce bitrate" patented technology

A decoding device according to the present disclosure is a decoding device (100) that decodes core encoded data where a low-band spectrum of a predetermined frequency or lower has been encoded, and extended band encoded data where a high-band spectrum of a predetermined frequency or higher has been encoded based on core encoded data. The decoding device includes: an amplitude normalization unit (103) that normalizes the amplitude of the core decoded spectrum, obtained by decoding the core encoded data, by the largest value of the amplitude of the core decoded spectrum, and generates a normalized spectrum; a noise generating unit (104) that generates a noise spectrum; a first addition unit (105) that adds the noise spectrum to the normalized spectrum and generates a noise-added normalized spectrum; and an extended band decoding unit (106) that decodes the extended band encoded data using the noise-added normalized spectrum, and generates a noise-added extended band spectrum.

An encoding apparatus and method and a decoding apparatus and method are provided. A method for decoding a motion vector according to an embodiment is disclosed, the method comprising the steps of determining at least one PMV candidate block for determining a prediction motion vector of a current block; determining availability of motion vectors of the at least one PMV candidate block; if there is a PMV candidate block determined as unavailable, determining a prediction motion vector of the current block by using a base motion vector (MV); and obtaining a motion vector of the current block based on the determined prediction motion vector.

This invention relates to the field of remote sensing image compression technology, specifically to a remote sensing image compression method based on dual-tree complex wavelet convolution and a frequency dictionary entropy model. The method includes: compressing remote sensing images using a remote sensing image compression model based on dual-tree complex wavelet convolution and a frequency dictionary entropy model; the remote sensing image compression model includes a dual-tree complex wavelet convolution module, a frequency dictionary entropy model module, and a residual feature extraction module; the dual-tree complex wavelet convolution module is used to perform downsampling and upsampling feature processing on the remote sensing image, effectively removing frequency domain redundancy in the latent representation; the frequency dictionary entropy model module is used to perform frequency division on the obtained latent representation of the remote sensing image to establish a probability model; the residual feature extraction module is used to extract features from the remote sensing image, effectively capturing long-range contextual information. This invention enhances the model's image compression effect by introducing dual-tree complex wavelet convolution and a frequency dictionary entropy model, significantly improving the fidelity of remote sensing images at high compression ratios.

The invention relates to a predictive method and apparatus for decoding, a predictive method for encoding, an encoding system, and a computer-readable storage medium. This method comprises the following steps: obtaining adjacent reference pixels at least one edge of the block to be decoded to obtain the first set of adjacent reference pixels; identifying the reference point from at least one edge, and determining the positions of the reference pixels to be selected corresponding to at least one edge according to a predefined number of samples; based on the positions of the reference pixels to be selected, selecting reference pixels corresponding to the positions of the reference pixels to be selected from the first set of adjacent reference pixels, and generating a subset of adjacent reference pixels from the selected reference pixels; and based on the subset of adjacent reference pixels, performing predictive decoding on the block to be decoded.

The application provides a stereo video compression method with double-branch attention, comprising the following steps: dividing a stereo video into a left video frame sequence and a right video frame sequence; inputting a video frame of the stereo video at time t, a time-adjacent reconstructed frame and a view-adjacent reconstructed frame of the video frame into a DAN stereo video compressor to obtain a video reconstructed frame at time t; wherein the DAN stereo video compressor comprises the following modules: a feature extraction module, a motion estimation module, a disparity estimation module, an LGEDB-based coding and decoding module, a motion compensation module, a disparity compensation module, a double-branch high-frequency information fusion module and an image reconstruction module; and the LGEDB and the DHFFM can realize higher-quality image reconstruction with the same or lower Bits Per Pixel (BPP).