Complex wavelet transforms offer the opportunity to perform directional and coherent processing based on the local magnitude and phase of signals and images. Although demising, segmentation, and image enhancement are significantly improved using complex wavelets, the redundancy of most current transforms hinders their application in compression and related problems. In this paper we introduce a...

Digital images are used everywhere and it is easy to manipulate and edit because of availability of various image processing and editing software. Resizing the image to a lower resolution can alter the appearance of an image. It is useful at times to create a downsampled version of the image that gives the same impression as the original. There are many methods for image downsampling. In this p...

Recently the Wavelet Transform has gained a lot of popularity in the field of signal and image processing. This is due to its capability of providing both time and frequency information simultaneously, hence giving a timefrequency representation of the signal. The traditional Fourier Transform can only provide spectral information about a signal. Moreover, the Fourier method only works for stat...

Filtering noise, in real time, has applications in speech and image processing. Considerable interest has arisen in recent years regarding filtering in the wavelet transform domain. This technique has been effective in noise removal with minimum side effects on important features such as image details and edges. In this paper, the effectiveness of both soft and hard thresholding for desired det...

-This paper proposes a novel image watermarking method in discrete wavelet transform domain using support vector machines. Reference and watermark images are used to modify the coefficients of the particular even and odd blocks of the wavelet transformed image. Good learning ability of SVMs are used to extract the watermark from the watermarked image even after several different image processin...

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...

An important step in image processing tasks involves the identiication of certain desired attributes in an image. Traditionally, this is done by transforming the image into a domain where the desired attributes or features are easily identiiable. In this paper, we discuss the parallel implementation of one such image transform{the 2-D Gabor based Wavelet Transform. Individual components of this...

Wavelet based methods get more and more widely used in image processing applications. This increases the need for standard image operations to be performed in the wavelet domain. As the wavelet transform lacks some basic properties such as shift invariance and a convolution theorem similar to the Fourier transform, this turns out to be a non trivial task. This work presents a strategy to implem...

Recently, several wavelet transform based image coding techniques are reported in literature. Though these schemes yield very low bit rates, they suffer from the drawback of computational complexity. There is always a need for simple, fast and easy to implement image coding techniques that yield good subjective quality at low bitrates. To obtain good data compression, the wavelet transform coef...

We introduce a new transform called the randlet transform and explore applications to universal perceptual image hashing (key-based randomized digests) and image identification. Our transform yields robust signal representations that are nearly invariant to several perceptually insignificant transformations (attacks, intentional or otherwise). Our signal representation is hard to guess without ...