Image-quality estimation based on supercomplex singular-value decomposition
A singular value decomposition and quality assessment technology, applied in the field of image processing, can solve the problems of ignoring color information and inability to effectively distinguish the distortion type of damaged color images, etc.
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[0058] Utilize method of the present invention respectively to six test images (Lena (Lina), Baboon (baboon Buddha), Peppers (pepper), Girl (girl), Airplane (aircraft), and Goldhill (Jinshan) image such as figure 1 shown) to produce five different distortion types: JPEG compression, Gaussian blur (Gaussian blur), Gaussian noise (Gaussian noise), Sharpening (sharpening), and DC-shifting (pixel translation), and each distortion type Five different distortion levels are included. The test results show that, compared with the currently known objective evaluation methods of color image quality (such as MSE, PSNR and MSSIM, etc.), the performance of this method is better.
[0059] Taking Lena and Baboon images as examples, firstly, different types and levels of distortion processing are performed on Lena and Baboon images, as shown in Table 1.
[0060] In Table 1, JPEG represents the image compressed by the JPEG method, G.noise represents the image with Gaussian noise added (Gaussi...
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