In this paper to introduce Symlets wavelet technique using 2-D DWT in image processing. The scope of the work involves compression and denoising, image clarity and to find the effect of the decomposition and levels of threshold and to find out energy retained (image recovery) and lost. The experiments and simulation is carried out on still image .jpg formats.
The wavelet differs in image clarity and energy retaining. Each method is compared and classified in terms of its efficiency at different decomposition and threshold levels. Therefore, the recovery of image is clarity and good, but the compression and energy retaining of percentage is different. In order to measure the performance of the de-noising, a noise is added to the still image and given as input to the de-noising algorithm, which produces an image close to the original image. Wavelet transformation is the technique that provides both spatial and frequency domain information but Fourier transforms only in frequency domain.
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