Shape Adaptive Discrete Wavelet Transform Research Articles

A New Approach to Region Based Image Retrieval using Shape Adaptive Discrete Wavelet Transform

In this paper, we present an efficient region-based image retrieval method, which uses multi-features color, texture and edge descriptors. In contrast to recent image retrieval methods, which use discrete wavelet transform (DWT), we propose using shape adaptive discrete wavelet transform (SA-DWT). The advantage of this method is that the number of coefficients after transformation is identical to the number of pixels in the original region. Since image data is often stored in compressed formats: JPEG 2000, MPEG 4…; constructing image histograms directly in the compressed domain, allows accelerating the retrieval operation time, and reducing computing complexities. Moreover, SA-DWT represents the best way to exploit the coefficients characteristics, and properties such as the correlation. Characterizing image regions without any conversion or modification is first addressed. Using edge descriptor to complement image region characterizing is then introduced. Experimental results show that the proposed method outperforms content based image retrieval methods and recent region based image retrieval methods

Multiview Image Coding Using Depth Layers and an Optimized Bit Allocation

In this paper, we present a novel wavelet-based compression algorithm for multiview images. This method uses a layer-based representation, where the 3-D scene is approximated by a set of depth planes with their associated constant disparities. The layers are extracted from a collection of images captured at multiple viewpoints and transformed using the 3-D discrete wavelet transform (DWT). The DWT consists of the 1-D disparity compensated DWT across the viewpoints and the 2-D shape-adaptive DWT across the spatial dimensions. Finally, the wavelet coefficients are quantized and entropy coded along with the layer contours. To improve the rate-distortion performance of the entire coding method, we develop a bit allocation strategy for the distribution of the available bit budget between encoding the layer contours and the wavelet coefficients. The achieved performance of our proposed scheme outperforms the state-of-the-art codecs for several data sets of varying complexity.

Shape adaptive wavelet transform for magnetic resonance images coding

Region-based coding is an important feature in today's image coding techniques as it follows different regions of the image that will be encoded at different bit rates and hence at different qualities rather than encoding the entire image with a single quality constraints. This article proposes an algorithm for the region-based coding of the brain magnetic resonance images in which the brain part will be encoded with more number of bits than the background. This method employs Shape Adaptive Discrete Wavelet Transform, which can transform the regions of interest and the background on the images independently and the coefficients can be encoded by using the SPIHT coding at different levels. This algorithm was compared with the existing wavelet-based coding techniques and a better PSNR was achieved for the same bit rate by reconstructing the region of interest with high quality than the background.

Performance Evaluation of Magnetic Resonance Images Coding Using Shape Adaptive Discrete Wavelet Transform

Region based coding is an important feature in today's image coding techniques as it follows different regions of the image will be encoded at different bit rates and hence at different qualities rather than encoding the entire image with a single quality constraints. This paper evaluates the features of using Shape Adaptive Wavelet Transform for the region based coding of the brain magnetic resonance images, in which the brain part will be encoded with more importance than the background. Shape Adaptive Discrete Wavelet Transform (SA-DWT) can transform the regions of interest and the background on the images independently and the coefficients can be encoded by using the SPIHT coding at different levels. This algorithm was compared with the existing wavelet based coding techniques and a better PSNR was achieved for the same bit rate by reconstructin g the region of interest with high quality than the background. lossless schemes and also maintain the quality of the image. Volumetric medical data are image sequences of any organ for the three dimensional view. These images are correlated both within and across slices to eliminate the redundancy. Some of the existing 3D compression techniques used motion compensation and encoded the image by the mesh formation. The deformation across the slices of the sequence is modeled as motion and the motion compensation algorithm is used to exploit the correlation between the slices (1). This method can provide a lossless compression of the sequence but with increased expense of complexity. Region based compression methods based on wavelet transforms can perform better with relatively less complexity. In JPEG 2000 part - 1 (2), max-shift ROI coding is used which exploits intra band dependency and adopts EBCOT (3) algorithm for coding the bit planes of wavelet coefficients. In this, it is not necessary to send the shape information as side information for decoding but the coefficients will blend with the pixels at the boundary between the ROI and the background. In JPEG 2000 part- 2 (4), scaling based ROI coding is adopted whereby the coefficients associated with the ROI are scaled up by a certain number of bitshift and then the bit planes of the coefficients are encoded plane by plane.

SPIHT-Based Coding of the Shape and Texture of Arbitrarily Shaped Visual Objects

A new scheme for coding both the shape and texture of arbitrarily shaped visual objects is presented. Based on set partitioning on hierarchical trees (SPIHT), the proposed Shape and Texture SPIHT (ST-SPIHT) employs a novel implementation of the shape-adaptive discrete wavelet transform (SA-DWT) using in-place lifting, along with parallel coding of texture coefficients and shape mask pixels to create a single embedded code that allows for fine-grained rate-distortion scalability. The single output code simplifies the logistics of object storage and transmission compared to previously published schemes. An input parameter provides control over the relative progression between shape and texture coding in the embedded code, allowing for adjustment of the emphasis of shape versus texture quality in low bit rate reconstructions. The combination of features provided by ST-SPIHT, namely, explicit and progressive shape coding in parallel with wavelet-based embedded coding of the object texture, is unique compared to previously published schemes. Computational complexity is minimized since the shape coding takes advantage of the decomposition and spatial orientation trees used for texture coding. Objective and subjective simulation results show that the proposed ST-SPIHT scheme has rate-distortion performance comparable or superior to MPEG-4 Visual Texture Coding for most bit rates

VLSI Architecture for Lifting-Based Shape-Adaptive Discrete Wavelet Transform with Odd-Symmetric Filters

In this paper, a VLSI architecture for lifting-based shape-adaptive discrete wavelet transform (SA-DWT) with odd-symmetric filters is proposed. The proposed architecture is comprised of a stage-based boundary extension strategy and the shape-adaptive boundary handling units. The former could reduce the complexity of multiplexers that are introduced to solve the shape-adaptive boundary extension. The latter consists of two multiplexers and can solve the shape-adaptive boundary extension locally without any additional register. Two case studies are presented, including the JPEG 2000 default (9, 7) filter and MPEG-4 default (9, 3) filter. According to comparison results with previous architectures, the efficiency of the proposed architectures is proven.

Object watermarks for digital images and video

The growth of new image technologies has created a need for techniques that can be used for copyright protection of digital images and video. One approach for copyright protection is to introduce an invisible signal, known as a digital watermark, into an image or video sequence. With the development of MPEG-4, frame-based approach has been migrating to object-based approach. Therefore, object-based watermarking schemes are needed. In this article, we propose a novel blind object watermarking scheme for images and video using shape adaptive-discrete wavelet transform (SA-DWT). To make the watermark robust and perceptual invisible, we embed it in the weighting mean of the wavelet blocks using the quantisation visual model based on the human visual system. Watermark detection is accomplished without the original, unwatermarked object by using statistical detection technique. Experimental results demonstrate that the proposed watermarking scheme is perceptual invisible and robust against many attacks such as lossy image/video compression (e.g. JPEG, JPEG2000 and MPEG-4), scaling, adding noise, filtering, D/A and A/D conversion, etc.

Arbitrarily shaped image coding by using translation invariant wavelet transforms

This study presents two sets of translation invariant wavelet transforms for coding an arbitrarily shaped image. Each set can be viewed as a shape-adaptive discrete wavelet transform (SA-DWT) with the property of translation invariance. The proposed transform schemes have the following merits: (1) they are translation invariant, (2) no sharp transition appears at the edges of the image, (3) the number of pixels is maintained constant after transformation, (4) the correlation of pixels is fully exploited, and (5) the property of self-similarity across scales is preserved.