This paper studies the adaptive wavelet design for fabric defect detection. In order to achieve translation invariance and more flexible design, the wavelet design focused on nonsubsampled wavelet transform. We design the wavelet filters under the constraints that the analysis filters are power complementary, and the wavelet has only one vanishing moment, which corresponds to a multiscale edge ...

Algorithms based on wavelet-domain hidden Markov tree (HMT) have demonstrated excellent performance for image denoising. The HMT model is able to capture image features across the scales, in contrast to classical shrinkage that thresholds subbands independently. In this work, we extend the aforementioned results to a lapped transform domain. Lapped Transforms (LT) are -channel linear phase filt...

In image compression, the motive is to reduce the data redundancy significantly, both in spatial and frequency domain, without much affecting the quality of the picture. Almost lossless reversible image compression model is proposed for both continuous and discrete time cases, exploiting integer wavelet transform(IWT) employing lifting scheme(LS).Unlike its conventional counterpart in wavelet d...

In recent years wavelets have been widely used for signal compression, image compression being a prime example, and for signal denoising. What makes wavelets such an attractive tool is their capability of representing both transient and stationary behaviors of a signal with few coefficients. In this paper we consider the problem of compressing and denoising a particular class of functions: piec...

This article presents results of image enhancement for robot vision. Results are obtained by superresolution techniques in wavelet domain. The calculated motion of wavelet coefficients in stationary image can enhance image quality. It can be used as interpolation information for increasing resolution. This is basis for wavelet quasi-superresolution, where one low-resolution image is interpolate...

The performance of subband image coders depends on the proper choice of filter banks. It is therefore desirable to find algorithms for optimizing the filter banks. A theory for finding jointly optimized analysis and synthesis filter banks with arbitrary filter lengths and arbitrary delay through the filter bank is proposed. Theoretical results are included. Comparisons are made against the well...

Several classes of images contain a clearly determined set of basic signals. This permits the development of signalmatched filter banks for image compression. A new approach for the derivation of signal-optimized filter banks using nonlinear optimization is presented here. Filters optimized with respect to the vessel and background signal of angiographic images are provided as a design example....

Wavelets, filter banks and multiresolution signal analysis, have been used independently in the fields of applied mathematics, computer vision and signal processing. It is interesting to note that they performed similar functions in different fields. It is recently, that they converged to form a single theory. In the paper, it is shown that the fundamental idea was the same in all the fields i....

In the computation of forward and inverse Discrete Wavelet Transform (DWT) using Cellular Neural Network (CNN), templates that mimic Haar wavelet are used. It is well known that Daubechies wavelet is the most popular wavelet used in the computation of DWT coefficients. This paper presents an approach towards the design of templates that mimic Daubechies wavelets. A global search algorithm, name...

In this paper we have used a previously reported adaptive filter bank structure for image decomposition and lossy reconstruction. We used a robust 2D windowed LS (LSW) adaptation algorithm to change the filter parameters and to adapt them to the local image properties. To improve the coding gain of the lossy image compression scheme, quantization of the adapted filter parameters has been explor...