Classification quantization coding method based on bi-orthogonal lapped transform
A technology of overlapping transformation and quantization coding, which is applied in the field of remote sensing image data transmission, can solve problems such as the difference in coding performance parameters and image coding performance
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Embodiment 1
[0057] (1) Establish a test image library with 15 images;
[0058] (2) Set the expected objective image quality PSNR to 35dB;
[0059] (3) Calculate the image activity value of the test image, and the quantization parameter value near 35dB after biorthogonal overlapping transformation and quantization inverse transformation. The results are shown in Table 1;
[0060] Table 1
[0061]
[0062]
[0063] (4) Define test images 1, 2, 3, 4, 5, 11, 12, 13, 14, and 15 as Class A according to the size of the quantization parameters, and test images 6 and 15 as Class B. Test images 7, 8, 9, and 10 are divided into category C;
[0064] (5) The image activity values of different test images are used as feature values for the training of support vector machines;
[0065] (6) The average quantization step length of the A-type test images is 47, the average quantization step length of the B-type test images is 59, and the average quantization step length of the C-type test images...
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