Image Processing using Wavelet Transform Based Noise Removal Filter

Image processing schemes which exhibits flexibility, adaptability and non-linearity are extremely useful for applications such as image transformation, correction of blurring effects, noise removal, histogram equalization etc. Images with random variations in Signal-to-Noise Ratio (SNR) can be treated with conventional adaptive filters. The demerits associated with adaptive filters are inability to cope with structural variations, limited performance to address low range noise spatial density (typically less than 0.2). This paper addresses these disadvantages and proposes a wavelet transform based filtering scheme for image processing. This scheme uses Peak Signal-to-Noise Ratio (PSNR) as performance metric and the results shows a higher PSNR was yielded by the scheme.