SVD Based Poor Contrast Improvement of Blurred Multispectral Remote Sensing Satellite Images

Abstract

In this letter, analyze the satellite images by using discrete cosine transform and singular value decomposition. The proposed technique presents an advance multiband satellite colour, contrast improvement technique of a poor-contrast satellite images. The input image is decomposed into the two frequency sub bands by using DCT and estimates the singular value matrix of the lowâ"low sub band image and then it reconstructs the enhanced image by applying inverse DCT. This technique is useful for the betterment of the INSAT as well as LANDSAT satellite image for the feature extraction purpose. The singular value matrix represents the intensity information of the given image and any change on the singular values change the intensity of the input image. The proposed technique converts the image into the DCT-SVD domain and after normalizing the singular value matrix, the enhanced image is reconstructed by using IDCT. The visual and quantitative results suggest that the proposed DCT-SVD method clearly shows the increased efficiency and flexibility of the proposed method over the exiting methods such as the Decor relation Stretching, Linear Contrast Stretch, GHE and DWT-SVD based techniques. The experimental results show the superiority of the proposed method over conventional methods.