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A Measurement Domain Compressed Sensing Coding Algorithm Based on Neighboring Pixel Correlation

A technology of compressed sensing and adjacent pixels, which is applied in image communication, climate sustainability, advanced technology, etc. It can solve the problems of breaking the spatial adjacent correlation of pixel domain, obstacles to the practical application of compressed sensing, and the inability to directly apply coding algorithms, etc. , to achieve the effects of easy hardware implementation, high reconstructed image quality, and reduced data volume

Active Publication Date: 2022-05-20
FUDAN UNIV
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Problems solved by technology

Since the output of the compressed sensing sensor is the measured value instead of the pixel, which breaks the spatial neighbor correlation in the pixel domain, the traditional pixel-based coding algorithm cannot be directly applied, which poses a great obstacle to the practical application of compressed sensing.

Method used

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  • A Measurement Domain Compressed Sensing Coding Algorithm Based on Neighboring Pixel Correlation
  • A Measurement Domain Compressed Sensing Coding Algorithm Based on Neighboring Pixel Correlation
  • A Measurement Domain Compressed Sensing Coding Algorithm Based on Neighboring Pixel Correlation

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Embodiment Construction

[0030] Combined with the schematic diagram, the image is taken as an example of 8×8 blocks to further describe the present invention.

[0031] According to the compressed sensing theory, the original image data is passed through the measurement matrix to obtain the measurement value. During this process, the pixel value in the pixel domain is transformed into the measurement value in the measurement domain, and the amount of data is reduced. Process such as figure 2 Shown: The measurement value is the linear combination of pixels in the image block, and the design of different measurement matrices corresponds to different combination methods. Assuming the target compression rate is R, each image block contains N B pixel values, need to get M B measured values ​​instead of pixel values, where M B =round(N B ×R), this M B measured values ​​by M B ×N B The measurement matrix and N of B ×1 pixel matrix is ​​multiplied to produce, where N B =64.

[0032] Number of known ...

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Abstract

The invention belongs to the technical field of compressed sensing, in particular to a measurement domain compressed sensing coding algorithm based on the correlation of adjacent pixels. The present invention first uses the deterministic measurement matrix based on the correlation of adjacent pixels to obtain the measurement value of the image block, embeds the pixel domain boundary information of each block into the measurement domain, and then uses the measurement value at the edge of the block to predict the adjacent segmentation. The measured value of the block; then quantize and encode the residual between the measured value and the predicted value, and generate a coded bit sequence for transmission. The invention can effectively reduce the transmission bit rate of compressed sensing images, effectively reduce data bandwidth, reduce hardware overhead, and improve image reconstruction quality.

Description

technical field [0001] The invention belongs to the technical field of compressed sensing, and in particular relates to a measurement domain compressed sensing coding algorithm based on the correlation of adjacent pixels. Background technique [0002] Since compressed sensing can break through the limitation of sampling frequency by Nyquist law in traditional sampling, in recent years, compressed sensing theory has developed rapidly in various signal acquisition and processing fields. In the CMOS image sensor based on compressive sensing, the image signal which is approximately sparse in the transform domain is sampled at a lower sampling rate, and the low-dimensional measurement value, that is, the linear combination of pixels, can be obtained. In this process, sampling and compression are realized at the same time, and N pixels can be replaced by M measured values. The advantage of compressed sensing is that less data volume reduces the throughput rate and power consumpti...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H04N19/176H04N19/159H04N19/42H04N19/91H04N19/96H04N19/147
CPCH04N19/176H04N19/159H04N19/42H04N19/91H04N19/96H04N19/147Y02D30/70
Inventor 范益波万仁涛
Owner FUDAN UNIV
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