Two-dimensional discrete wavelet transform (DWT) for processing image is conventionally designed by line-based architectures, which are simple and have low complexity. However, they suffer from two main shortcomings the memory required for storing intermediate data and the long latency of computing wavelet coefficients. This work presents a new block-based architecture for computing lifting-bas...

This paper proposes an automatic registration technique based on steerable pyramid transform and robust shift invariant feature transform (SIFT) features, which can deal with the large variations of scale, rotation and illumination of the images. First, the steerable pyramid transform is used to the two input images and the sub-band images along certain orientations are obtained at each layer. ...

This paper presents adaptive edge detector using a novel directional wavelet transform. The proposed algorithm has two stages: a) directional wavelet transform and b) edge detection on space–scale– directional plane with maximum entropy measure. Preliminary results with synthetic images show that directional wavelet transforms gives excellent results. The proposed method was tested on synthetic...

Retrieval of texture images, especially those with different orientation and scale changes, is a challenging and important problem in image analysis. This paper adopts spiking cortical model (SCM) to explore geometrical invariant texture retrieval schemes based on Discrete Cosine Transform (DCT) coefficients of pulse images. The series of pulse images, outputs of SCM, have a robust talent for e...

An orthogonal discrete wavelet transform (DWT) is a slantlet transform (SLT) with two zero moments and having improved time localization. SLT retains usual characteristics of filter bank implementation with a scale dilation factor of two. The basis is based on filter bank which uses different filters for different scales, is piecewise linear unlike iterated filter bank in DWT. This paper discus...

Wavelet denoising techniques are used to remove additive Gaussian noise by thresholding the wavelet coe cients. Like other transform based lters, wavelet shrinkage methods provide blur or visual artifacts that are exhibited in the neighborhood of image edges. The motive for implementing the Hybrid Wavelet Transform Filter (HWTF) is to provide discriminate smoothing operator for noise removal. T...

Multi-resolution analysis of digital image has attracted numerous studies since dyadic wavelet transform was introduced to this field. Aiming at achieving accurate and stationary edge detection, an improved Mallat wavelet decomposition algorithm was employed. This algorithm was defined by a low frequency component and three high frequency components. Two-dimensional signal can be reconstructed ...