57 results about "Digital image compression" patented technology

A system and method for generating a second reduced size digital image from a first digital image, the method including iteratively compressing the first digital image to an extent determined by a quality measure comprising at least a blockiness measure quantifying added artifactual edges along coding block boundaries of the second image and/or use of a quantization matrix generated by computing a weighted average of the quantization matrix of the first digital image and a scaled second quantization matrix.

A method for the prior monitoring of the detectability of a watermarking signal inserted by modulation in a set of coefficients representing for example a digital image. The method comprises the step of simulating a distortion on the set of modulated coefficients, the distortion corresponding to a given compression level of the set of coefficients before modulation, determined by optimisation of a ratio of transmission rate to distortion. The method further comprises the step of calculating a detectability test on the set of modulated coefficients after distortion, and a step of comparing the detectability test with a threshold detection value. The method is used notably for inserting a watermarking signal during the compression of a digital image.

Methods and systems for compression of digital images (still or motion sequences) are provided wherein predetermined criteria may be used to identify a plurality of areas of interest in the image, and each area of interest is encoded with a corresponding quality level (Q-factor). In particular, the predetermined criteria may be derived from measurements of where a viewing audience is focusing their gaze (area of interest). In addition, the predetermined criteria may be used to create areas of interest in an image in order to focus an observer's attention to that area. Portions of the image outside of the areas of interest are encoded at a lower quality factor and bit rate. The result is higher compression ratios without adversely affecting a viewer's perception of the overall quality of the image.

The invention discloses a digital image compressing, encrypting and encoding combined method, and belongs to the technical field of image encrypting. The method is achieved on the basis of the JPEG compressing and encoding standard which is most widely applied at present, and the encrypting algorithm based on chaos is integrated with the encoding process; according to the characteristic that DC coefficients and AC coefficients are separately encoded on the basis of the JPEG standard, the DC coefficients and the AC coefficients of an image are separately encrypted; in order to give consideration to both security and compressing efficiency, all the DC coefficients and part of the AC coefficients are encrypted through the method, coefficients at the same positions in all DCT blocks are divided into different groups and are scrambled and diffused within the groups, and damage to differential encoding and run length encoding in the encrypting process is reduced as much as possible; scrambling and diffusing are achieved on the basis of logistic chaotic mapping and Chebyshev chaotic mapping respectively. The experiments prove that the method has high data compressing capacity while providing effective image data security protection.

Disclosed is an image encoder that divides a digital image into a set of “macroblocks.” Each macroblock is encoded by applying spatial (and possibly temporal) prediction. The “residual” of the macroblock is calculated as the difference between the predicted content of the macroblock and the actual content of the macroblock. The residual is then “decimated” by taking an orderly subset of its values. The decimated residual is then either transmitted to an image decoder or is stored for later use. To recreate the original image, the macroblocks are first recreated from their received residuals. When a decimated residual is received, the values of the residual left out during decimation are interpolated from the values actually received. Using the prediction techniques along with the residual, the original content of the macroblock is recovered. The macroblocks are then joined to form the original digital image.

The invention provides a BP neural network digital image compression based image watermark embedding and extracting method. The method includes: S1a, performing scrambling treatment on an original watermark image to acquire the scrambled watermark image; S2a, establishing a BP neural network and setting transfer function, training adjustment function, the number of training, neuron activation function thresholds, learning constant and compressibility factors of the BP neural network; S3a, dividing the scrambled watermark image into image embedding blocks, setting input and output expectations as carrier image blocks, and training the carrier image blocks through the BP neural network to acquire output O of a hidden layer; S4a, embedding watermarks in the output O of the hidden layer, and decompressing compressed images embedded with watermark image information to obtain carrier images embedded with the watermarks. The invention further provides a BP neural network digital image compression based image watermark extracting method.

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.

This image compression applies a lossless compression algorithm and a lossy compression algorithm to code the differential value of the adjacent pixels. If lossy algorithm is selected, it codes the differential value of the present pixel and the reconstructed previous pixel. In quantizing the differential value of adjacent pixel components, a variable range of interval of value is predetermined with smaller interval range in values closer to “0” and larger interval range farer from “0”. The region with less mean variance, less quantization error will be allowed and the region with larger mean variance, more quantization error is allowed

Disclosed is an image encoder that divides a digital image into a set of “macroblocks.” If appropriate, a macroblock is “downsampled” to a lower resolution. The lower-resolution macroblock is then encoded by applying spatial (and possibly temporal) prediction. The “residual” of the macroblock is calculated as the difference between the predicted and actual contents of the macroblock. The low-resolution residual is then either transmitted to an image decoder or stored for later use. In some embodiments, the encoder calculates the rate-distortion costs of encoding the original-resolution macroblock and the lower-resolution macroblock and then only encodes the lower-resolution macroblock if its cost is lower. When a decoder receives a lower-resolution residual, it recovers the lower-resolution macroblock using standard prediction techniques. Then, the macroblock is “upsampled” to its original resolution by interpolating the values left out by the encoder. The macroblocks are then joined to form the original digital image.

The present invention provides method and apparatus of image buffer compression for video bit stream encoding. At least one re-constructed referencing frame pixel is compressed again and stored in a storage device. During motion estimation of a video compression, a decompressing engine recovered pixels of the predetermined searching range for best match block searching. In the still image compression, a lossless compression algorithm is applied to compress pixel data of at least one line of pixels and to save the compressed pixels into a storage device, decompression mechanism recovers at least one pixel of at least one line of pixels for predicting the value of a target pixel.

A method for compressing a digital image composed of a matrix of pixels to provide a compressed digital representation of said image of a predetermined size, the quality of the compressed digital representation being affected by a compression quality factor Q and the method including the fol-lowing steps: for a particular image producing device, developing a mathematical model defining a relationship between the content of the digital image and Q, developing said mathematical model by repeatedly compressing a set of digital test images with varying Q until each test image is compressed to a predetermined size, determining a metric M representing the content of the digital image, applying said metric M in said mathematical model to obtain an image determined quality factor Qmod and compressing the digital image using said quality factor Qmod.

The invention relates to a method of compressing a digital representation of an image by storing the image in a plurality of sampling quality levels in a progressive manner, with higher quality levels needing only to be included on the basis of adjacent lower quality levels The incremental part is enough, and the data on each quality level must be transformed, quantized and entropy coded. The discrete wavelet cosine transform provided in the present invention combines the frequency domain transform characteristics of the discrete cosine transform and the space domain transform characteristics of the wavelet transform. The sampling quality level sequence provides a multi-resolution representation for images, and the present invention also proposes a novel context selection method to handle different color components and coefficients in different positions, and can be used on the Internet to Images at a given quality level are decompressed in progressive mode, and get progressive download and transfer effects.

The invention discloses an image lossless compression method based on a discrete Tchebichef orthogonal polynomial, and belongs to the technical field of digital image compression. According to encoding and decoding methods, two-dimensional forward/backward orthogonal transformation is performed through two-dimensional integer forward/backward discrete Tchebichef orthogonal polynomial transformation instead of other integer transformation methods adopted in the prior art, so that lossless compression is realized; the problem of mismatch of an encoder can be solved effectively; lossless encoding is realized; and relatively high compression performance and higher extensibility are achieved. Mapping from integers to integers is realized in matrix transformation, and in-situ calculation is performed, so that images are reconstructed completely; hardware resource consumption is lowered; and hardware implementation is facilitated.

The invention relates to an electrical equipment X ray digital image processing algorithm support system. The support system comprises an X ray digital image collection interface, an X ray digital image denoising algorithm module, an X ray digital image sharpening algorithm module, an X ray digital image coloring algorithm module, an X ray digital image compression algorithm module, an X ray digital image partition algorithm module, an X ray digital image sorting algorithm module, an X ray digital image splicing algorithm module, and an X ray digital image recognition library module. The support system provided by the invention has the beneficial effects of simple structure, high efficiency of image processing, and high picture fidelity after treatment.

The invention relates to a two-dimensional discrete wavelet transform circuit and an image compression method using the same. The circuit and the method aim to solve the problem that massive intermediate data is required to be stored and the meeting of time sequence requirements is complex because the line transformation and column transformation of a conventional very large scale integrated circuit (VLSI) architecture are separated in a discrete wavelet transform link to cause the internal structural complexity of a VLSI and a low hardware utilization rate, and are used for image compression. In the discrete wavelet transform circuit, link scanning filtering and column scanning filtering are performed on pixels in an image at the same time by adopting four digital filters, so that the problems that the massive intermediate data is required to be stored and that the meeting of the time sequence requirements is complex due to the adoption of a way of sequentially performing line scanning transformation and column scanning transformation in the prior art. By the image compression method, the two-dimensional discrete wavelet transform circuit provided by the invention is adopted to effectively eliminate blocking effects, improve digital image compression processing efficiency and increase digital image compression processing speed.

A method for compressing a sequence of digital images includes: comparing a reference image of the sequence of digital images to a subsequent image of the sequence of digital images. In response to the reference and subsequent images being the same within a predetermined threshold, 1) a count of a number of images discarded is incremented, 2) the subsequent image is discarded, and 3) the comparing step is repeated with a next subsequent image. In response to the reference and subsequent images not being within the predetermined threshold, 1) the count is initialized and 2) the comparing step is repeated using the subsequent image as the reference image. Rather than comparing whole images corresponding portions of the images can be compared and compressed independently.

A surveillance system, an image compression serializer and an image decompression deserializer are disclosed. The Surveillance System includes a video camera, a coaxial cable and a central control machine. The video camera provides a real time record and has an image compression serializer which compresses a digital image, captured by the video camera, down to a specific resolution and converts the digital image of the specific resolution into a serial format. The coaxial cable couples the image compression serializer to an image decompression deserializer of the central control machine. The digital image in the specific resolution and serial format is conveyed to the image decompression deserializer to be converted into a parallel format and decompressed to be video encoded.

The invention, which belongs to the technical field of digital image compression, makes a request of protection of a discrete-Krawtchouk-orthogonal-polynomial-based image lossless compression method. When two-dimensional forward/reversed orthogonal transformation according to coding and decoding methods, two-dimensional integer forward/reversed discrete Krawtchouk orthogonal polynomial transformation is used for replacing other integer transformation methods used in the prior art, thereby realizing lossless compression; and a problem of encoder mismatching can be effectively solved. Besides, the compression performance and the extendibility are good. Mapping from an integer to an integer is realized by matrix transformation; calculation is carried out between home positions and an image can be reconstructed completely, thereby reducing the hardware resource consumption and realizing the hardware well.

The invention relates to the Bell template digital image compression technology, in particular to a Bell template digital image coder and decoder (CODEC) method based on the W-Z structure. The problem of that a quainter design existing in the existing Bell template digital image CODEC method is not for global optimization and the like is resolved. The Bell template digital image coder and decoder (CODEC) method includes steps as follows that (I), a frame of the Bell template digital image is converted to four component images through the color spatial isolation, pixels in each Bell template is in color spatial conversion, original pixel values are displaced luminance components Y 1, Y 2, original reddish blue pixel values are displaced aberration components C r, C b, then the luminance components Y 1,Y 2 and the aberration components C r, C b are respectively separated and similar combinations are rectangular two luminance component image A, B and two aberration component image C, D. The Bell template digital image CODEC method based on the W-Z structure is reasonable in design and capable of displaying better rate-distortion performance under the condition with high speeds.

In a method of digital image compression, the spatial frequency content of a digital image is characterized using a relatively sparse sampling of data blocks from the image, and a quantization table is constructed based on the characterization of the spatial frequency content.

A system and method of performing digital image compression comprises comparing pixels in various locations in a digital picture image frame; coding a position of pixels located in a foreground of the digital picture image frame; sending the coded positions of the pixels located in a foreground of the digital picture image frame to a frame buffer of a sprite controller; separating a background pixel group from a foreground pixel group in the digital picture image frame based on the coded positions; compressing the pixels in the foreground pixel group; and transmitting a frame number and a frame buffer parameter dimension corresponding to the compressed pixels to a digital picture image display viewer.