This paper presents parallel algorithms for computing multi-dimensional wavelet transforms on both shared memory and distributed memory machines. Traditional data partitioning methods for n-dimensional Discrete Wavelet Transforms (DWTs) call for data redistribution once a one dimensional wavelet transform is computed along each dimension. To avoid the data communication inherent in this redistr...

This paper addresses the most relevant aspects of lossy image coding techniques, and presents an evaluation study on this subject, using several transforms and different methods in the transform domain. We developed different transform based image coders/decoders (codecs) using different transforms, such as the discrete cosine transform, the discrete wavelet transform and the S transform. Besid...

The 2-D discrete wavelet transform (DWT) can be found in the heart of many image-processing algorithms. Until recently, several studies have compared the performance of such transform on various shared-memory parallel architectures, especially on graphics processing units (GPUs). All these studies, however, considered only separable calculation schemes. We show that corresponding separable part...

This paper extends the group testing for wavelets (IEEE Trans. Image Process. 11 (2002) 901) algorithm to code coefficients from the wavelet packet transform, the discrete cosine transform, and various lapped transforms. Group testing offers a noticeable improvement over zerotree coding techniques on these transforms; is inherently flexible; and can be adapted to different transforms with relat...

In this paper, we introduce vector-valued multiresolution analysis and vector-valued wavelets for vector-valued signal spaces. We construct vector-valued wavelets by using paraunitary vector lter bank theory. In particular, we construct vector-valued Meyer wavelets that are band-limited. We classify and construct vector-valued wavelets with sampling property. As an application of vector-valued ...

We present a preliminary investigation of compression of segmented 3D seismic volumes for the rendering purposes. Promising results are obtained on the base of 3D discrete cosine transforms followed by the SPIHT coding scheme. An accelerated version of the algorithm combines 1D discrete cosine transform in vertical direction with the 2D wavelet transform of horizontal slices. In this case the S...

The two-dimensional discrete cosine transform (DCT) can be found in the heart of many image compression algorithms. Specifically, the JPEG format uses a lossy form of compression based on that transform. Since the standardization of the JPEG, many other transforms become practical in lossy data compression. This article aims to analyze the use of these transforms as the DCT replacement in the J...

Digital image compression with multiresolution singular value decomposition is compared with discrete cosine transform, discrete 9/7 biorthogonal wavelet transform, Karhunen–Loève transform, and combinations thereof. The coding methods used SPIHT and run-length with Huffmann coding. The performances of these methods differ little from each other. Generally, the 9/7 biorthogonal wavelet transfor...

Image compression is a method through which we can reduce the storage space of images, videos which will helpful to increase storage and transmission process’s performance. In image compression, we do not only concentrate on reducing size but also concentrate on doing it without losing quality and information of image. In this paper, we present the comparison of the performance of Discrete cosi...

Corresponding Author: Shanthini Pandiaraj Department of Electronics and Media Tech., Karunya University, Coimbatore, India Email: [email protected] Abstract: This study presents an experimental evaluation of Discrete Wavelet Transforms for use in speaker identification. The features are tested using speech data provided by the CHAINS corpus. This system consists of two stages: Feature extract...