A wavelet transform method for coding film-grain noise corrupted images

We propose an algorithm for compressing images corrupted by film-grain type noise. The algorithm nonlinearly modifies the transform coefficients of noisy data for reducing the impact of noise on compression. Although any orthogonal transform is suitable for the application, the orthogonal wavelet transform is preferred for simplicity in calculating the filter coefficients and for obtaining better compression performance. The algorithm is tested on different images at different noise variances and the results are compared to spatial filtering before compression. Our method outperforms spatial prefiltering in terms of PSNR values and it is easier to implement