Image Zooming Using Wavelet Coefficients

Abstract

The work in this dissertation involves an algorithmic approach to zoom a given image in wavelet domain and to get a sharper image using with various interpolation techniques. The exploration is an attempt to develop quantitative measures that can automatically predict perceived image quality. An objective image quality metric can play a variety of roles in image processing applications. First, it can be used to dynamically monitor and adjust image quality; second, it can be used to optimize algorithms and parameter settings of image processing systems. Second, it can be used to benchmark image processing systems and algorithms as zoomed images are sharper as compared to other methods. Hence keeping all this in mind on this source of information, Discrete Wavelet Transform (DWT) with various interpolation techniques had been applied upon variances to obtain their values. Performance is measured by calculating Peak Signal to Noise Ratio (PSNR), and the proposed method gives much better PSNR compared to other methods. This algorithm can help in medical science to get the minutest details for detection of cancer.