A Novel Statistical and DCT based Image Encoder

P.B. Zadeh, T. Buggy, A.S. Akbari, and J.J. Soraghan (UK)


Discrete cosine transform, image compression, perceptual weights, quadtree coding, statistical parameters.


This paper presents a novel statistical and discrete cosine transform (DCT) based image-coding scheme. The proposed coding scheme divides the input image into a number of non-overlapping pixel blocks. The coefficients in each block are then decorrelated into their spatial frequencies using a discrete cosine transform. Coefficients with the same spatial frequency at different blocks are put together to generate a number of matrices, where each matrix contains coefficients of a particular spatial frequency. The matrix containing DC coefficients is losslessly coded to preserve visually important information. Matrices, which consist of high frequency coefficients, are coded using a novel statistically based coding algorithm developed in this paper. Perceptual weights are used to regulate the threshold value required in the coding process of the high frequency matrices. The proposed coding scheme and JPEG were applied to Lena, Elaine and House, three test images, and results show that the proposed coding scheme outperforms JPEG subjectively and objectively at low compression ratios. Results also indicate that the decoded images using the proposed codec have superior subjective quality at high compression ratios while JPEG suffers from blocking artifacts at high compression ratios.

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