Wavelet theory has been extensively developed in the function space L2 and discrete wavelet transform has successful applications in many areas. However, to understand better the performance of different discrete wavelet transforms, it is important to investigate their underlying discrete wavelet systems in l2. Though some preliminary results have been found recently, despite the fact that stab...

The Discrete Wavelet Transform (DWT) has two parameters: the mother of wavelets and the number of iterations. Selecting different parameters for different DWT of the same signal, different energy concentrations in the wavelet domain are obtained. So, for a particular signal there is a better pair of parameters that realizes the best energy concentration in the wavelet transform domain. In appli...

This paper presents simple wavelet based image compression method where wavelet transform is generated from orthogonal component transforms. Wavelets of DCT, DST and Real-DFT and Discrete Hartley Transform (DHT) are generated. Each generated wavelet transform is applied separately on R, G, and B plane of 256x256x3 colour image. Performance of these wavelet transforms is evaluated using two para...

This paper proposes novel lossy image compression technique using hybrid wavelet transform and vector quantization. First hybrid wavelet transform consisting of two different component transforms is generated and applied on color images. Discrete Kekre transform (DKT) and Discrete Cosine transform (DCT) play role of base and local transform respectively in hybrid wavelet transform. In transform...

The fast development of digital image processing leads to the growth of feature extraction of images which leads to the development of Image fusion. Image fusion is defined 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...

This paper proposes a discrete wavelet-based stereo matching technique. A discrete wavelet transform is first applied to a pair of stereo images to decorrelate the images into a number of approximations. Information in the basebands is less sensitive to shift variability of the wavelet transform. A self-adapting dissimilarity measure is employed to generate a disparity map of the stereo pairs. ...

This paper proposes a hardware-efficient architecture design of wavelet-based adaptive visible watermarking. Our method adopts discrete wavelet transform (DWT) to embed visible watermarking. We perform this algorithm using hardware-efficient architectures that combine operational reduction and resource sharing techniques. Our method provides high quality visible watermarking image and small har...

This paper proposes a discrete wavelet-based stereo matching technique. A discrete wavelet transform is first applied to a pair of stereo images to decorrelate the images into a number of approximations. Information in the basebands is less sensitive to shift variability of the wavelet transform. A self-adapting dissimilarity measure is employed to generate a disparity map of the stereo pairs. ...

Image compression plays a vital role in digital image processing. The need for image compression becomes apparent when number of bits per image are computed resulting from typical sampling rates and. quantization methods. For example, the amount of storage required for given images is (i) a low resolution, TV quality, color video image which has 512 x 512 pixels/color,8 bits/pixel, and 3 colors...

This paper proposes a discrete wavelet-based stereo matching technique. A discrete wavelet transform is first applied to a pair of stereo images to decorrelate the images into a number of approximations. Information in the basebands is less sensitive to shift variability of the wavelet transform. A self-adapting dissimilarity measure is employed to generate a disparity map of the stereo pairs. ...