Hybrid algorithms based on transforms for denoising satellite images

Abstract

— The image acquired from a sensor is always degraded by some form of noise. The noise can be estimated and removed by the process of denoising. Recently, the use of Hybrid Algorithms for denoising have gained popularity. The most commonly used transformation are Discrete Cosine Transform (DCT) and Discrete Wavelet Transform (DWT). DCT has the property of more energy compaction and requires less resources for computational whereas DWT is a multiresolution transformation. The proposed Hybrid Algorithms take advantage of both of the algorithms and this reduces the false contouring and blocking articrafts effectively. In this paper, the Hybrid Algorithms are evaluated for various images by comparing in terms of Mean Square Error, Peak Signal to Noise Ratio, Coefficient of Variance, Structural Similarity Index and Mean Structural Similarity Index.