Abstract

Previously¹ we introduced the use of the maximum entropy principle (MEP) for image reconstruction of moment-coded images. The MEP and the minimum relative principle (MREP) are used in reconstructing images previously compressed by retaining a subset of the coefficients of their discrete cosine transform (DCT), a popular method of image compression since it approximates closely the ideal Karhunen-Loeve transform compression. The normal way to reconstruct such compressed images is by using the inverse DCT. The reconstructed image under the MEP is the one that maximizes the entropy of the image subject to constraints reflecting the retained DCT coefficients. Under the MREP, the reconstructed image is obtained by successive minimization of its relative entropy subject to one constraint at a time, with each solution serving as a prior for the next minimization. Both methods were applied to images compressed by DCT, and the results were compared to normal inverse DCT reconstruction. It is concluded that MEP and MREP are better than IDCT, and the improvement is attributed to the fact that these methods make no assumptions about the value of the unretained coefficients, while IDCT assumes them equal to zero.

© 1987 Optical Society of America