An efficient wavelet based de-blocking algorithm for highly compressed images

In this paper, a novel post-processing method is proposed in wavelet domain for the suppression of blocking artifacts in compressed images. The novelty of new method is that we can obtain soft-threshold values based on the difference between the wavelet transform coefficients of image blocks and the coefficients of the entire image and threshold high frequency wavelet coefficients in different subbands using different values and strategies. The threshold value is made adaptive to different images and characteristics of blocking artifacts. In particular, the new method is robust, fast and works remarkably well for different DCT based compressed images at low bit rate. The method is nonlinear, computationally efficient and spatially adaptive. Another advantage of the new method is that it retains sharp features in the images after it removes artifacts. Experimental results show that the proposed method can achieve a significantly improved visual quality in the images, and also increase PSNR in the output image. The algorithm can be used for real-time post-processing in DCT-based encoders and decoders.