Time-frequency analysis is a powerful tool for signal analysis and processing. The Fourier transform and wavelet transforms are used extensively as is the Short-Time Fourier Transform (or Gabor transform). In 1996 the Stockwell transform was introduced to maintain the phase of the Fourier transform, while also providing the progressive resolution of the wavelet transform. The discrete orthonorm...

It is proposed that a new image enhancement scheme using wavelet transform, smooth and sharp approximation of a piecewise non linear filter technique after converting the RGB (Red, Green, and Blue) values of each pixel of the original image to HSV (Hue, Saturation, and Value). Wavelet transform is then applied to the luminance value of V component, it decomposes the input image into the four su...

In this paper, a method of super-resolution image reconstruction based on wavelet transform and edge-directed interpolation is put forward. Firstly the low resolution image is decomposed by the stationary wavelet transform; meanwhile, the image obtained from edge-directed interpolation is decomposed by discrete wavelet transform, then the three high frequency sub bands obtained through stationa...

In the production of medical images, noise reduction and contrast enhancement are important methods to increase qualities of processing results. Wavelet transforms have shown promising results for localization in both time and frequency, and hence have been used for image processing applications including noise removal. By using the edge-based denoising and adaptive nonlinear histogram stretchi...

time lower than other similar performing objective measures.

Large size images consist of multiple bands data which occupies large space. Image compression becomes important for such large image or data’s to reduce the bandwidth in transmission over a network and in storage space. Wavelet transform is an efficient tool with some limitations for various image processing applications. And these limitations are overcome by complex wavelet transform. In this...

The definition of an atomic representation of the wavelet transform of a signal allows us to write the evolution law through scales for modulus maxima of the transform. Although this result is very general and useful for various fields of image processing, we focus on its application to signal and image compression. We propose a simple trick for taking advantage from the law without directly so...

Image fusion is defi ned as the process of combining two or more different images into a new single image retaining important features from each image with extended information content. There are two approaches to image fusion, namely spatial fusion and transform fusion and three levels namely pixel, feature and region level. In spatial fusion, the pixel values from the source images are direct...