Application of framelet transform and singular value decomposition to image enhancement

In this paper, a new satellite image enhancement technique based on framelet transform and Singular Value Decomposition (SVD) has been proposed. Framelet transform is used to decompose the image into one low frequency subband and eight high frequency subbands. The enhancement is done with regard of both resolution and contrast. To increase the resolution, low and high frequency subbands have been interpolated. In intermediate stage, estimating high frequency subbands has been proposed to achieve sharpness. All the subbands are combined by inverse framelet transform to get the high resolution image. To increase the contrast, framelet transform is combined with SVD. Singular values of the low frequency subband are updated and inverse transform is performed to get the enhanced image. The proposed technique has been tested on satellite images. The quantitative measures such as Peak Signal-to-Noise (PSNR), Structural Similarity Index Measure (SSIM), Universal Quality Index (UQI), Entropy, Quality_ Score are used and the visual results show the superiority of the proposed technique over the conventional and state-of-art image enhancement techniques. The time complexity indicates the proposed image enhancement is suitable for further image processing applications.