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A Color Image Compression Sampling and Reconstruction Algorithm

A color image, compression sampling technology, applied in image communication, digital video signal modification, electrical components, etc., can solve the problem of large measurement matrix and easy to exceed the computer, and achieve the effect of good image quality and less data volume

Active Publication Date: 2018-05-04
FUZHOU UNIV
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AI Technical Summary

Problems solved by technology

Majumdar proposed to use the principle of group sparsity to reconstruct the color image, which effectively improved the reconstruction quality of the color image, but the measurement matrix is ​​too large, and it is easy to exceed the computer's running memory in the simulation, so it can only be applied to small-sized color images.

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  • A Color Image Compression Sampling and Reconstruction Algorithm
  • A Color Image Compression Sampling and Reconstruction Algorithm
  • A Color Image Compression Sampling and Reconstruction Algorithm

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Embodiment Construction

[0029] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0030] Please refer to figure 1 , the present invention provides a kind of compressed sampling and reconstruction algorithm of color image, it is characterized in that:

[0031] The programming process includes the following steps:

[0032] Step A1: decomposing a color image into R channel, G channel and B channel;

[0033] Step A2: Decompose the R channel, G channel and B channel into three layers of wavelet respectively to obtain the corresponding wavelet transform coefficients, wherein the low frequency and high frequency components of each layer of the R channel are distributed as follows figure 2 As shown, other channels are also similar; the R channel is decomposed into R1 part, R2 part, R3 part and R4 part; the G channel is decomposed into G1 part, G2 part, G3 part and G4 part; the B channel is decomposed into Part B1, Part B2, Part B3 and Pa...

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Abstract

The invention relates to a color image compression sampling and reconstruction algorithm. A coding end decomposes a color image into R, G and B channels and respectively carries out wavelet transforming on each channel. For wavelet transforming coefficients of different layers, different sampling rates are used for measuring. The relevance of three channels is used to carry out set sparse reconstruction on the coding end. According to the invention, when the image is processed, less data are sampled, and the restored image quality is great; and compared with a traditional RGB independent reconstruction algorithm, the algorithm provided by the invention has the advantage that the peak signal to noise ratio is improved 1 to 2dB at low sampling rate.

Description

technical field [0001] The invention relates to a compression sampling and reconstruction algorithm of color images. Background technique [0002] Compressed sensing is a new type of information processing theory, which breaks through the limitation of Nyquist sampling theorem in traditional sampling, so that the signal can be sampled at a sampling rate much lower than Nyquist, while still having high probability at the decoding end. to reconstruct the original signal. [0003] At present, many scholars have studied the application of compressive sensing theory in grayscale images, but its application in color images is relatively rare. When most scholars apply compressed sensing to color images, they transform the color image into RGB or YUV color space, thereby decomposing it into three independent channels, and then use the compressive sensing theory of grayscale images to process the three channels separately. Compression and reconstruction. However, using this method...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H04N19/186H04N19/166H04N19/132H04N19/63
Inventor 陈建苏凯雄杨秀芝朱宝珠
Owner FUZHOU UNIV
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