Compressed sensing image decoding method based on non-uniform quantizing noise model
A technology of quantization noise and compressed sensing, applied in the field of image decoding, which can solve the problems of low quality of reconstructed images at the decoding end and suboptimal signal reconstruction results.
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[0052] The compressed sensing decoding method is divided into two important steps of observation and reconstruction. The image compression decoding standard consists of two links: encoding and decoding. The present invention regards the transformation in encoding as CS observation, and the transformation matrix is equivalent to observation matrix, and replaces the inverse transformation in decoding with CS reconstruction, and ε is an error caused by quantization noise. Obviously, if the error ε can be accurately reconstructed, the convex set optimization method will obtain better reconstruction results than the inverse transformation.
[0053] It should be noted that in the specific implementation, the gradient sparse model is used to sparse the image, that is, the image signal x adopts the gradient sparse basis to make TV(x) sparse. In the following description, TV(x) means that x is in the gradient Sparse in meaning. Of course, any sparse base that can make the image spa...
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