Image Enhancement in the Compressed Domain Based on Retinex Theory

Existing image enhancement algorithms in the compressed domain can not preserve the details and color information when enhancing the contrast of images. They mostly treat the DCT coefficients uniformly using the same strategy, or can not inhibit artifacts if treating the coefficients differently. A new image enhancement algorithm in the DCT compressed domain based on Retinex theory is proposed. The algorithm divides DCT coefficients into the illumination component (DC coefficients) and the reflection component (AC coefficients) according to Retinex theory. The DC coefficients are adjusted to compress the image dynamic range by mapping the illumination component to an ideal range, using two simple but powerful functions. The AC coefficients which represent reflection component are adjusted to enhance the local details with a new definition of spectral content measure. The fact that perception of image detail information for peopleis based on the ratio of high and low frequency in human visual system leads to the new definition. The block artifacts will be suppressed using a block decomposing strategy with a threshold automatically according to the characteristics of the images to be enhanced. Compared with traditional Retinex and DCT enhancement algorithms, experiment results show the proposed algorithms efficiency in details enhancement and color preserving, also with artifacts compressed.