J. Zhu

Bio: J. Zhu is an academic researcher from University of Warwick. The author has contributed to research in topics: Image compression & Transform coding. The author has an hindex of 1, co-authored 1 publications receiving 67 citations.

Image compression using wavelets and JPEG2000: a tutorial

Abstract: The demand for higher and higher quality images transmitted quickly over the Internet has led to a strong need to develop better algorithms for the filtering and coding of such images. The introduction of the JPEG2000 compression standard has meant that for the first time the discrete wavelet transform (DWT) is to be used for the decomposition and reconstruction of images together with an efficient coding scheme. The use of wavelets implies the use of subband coding in which the image is iteratively decomposed into high- and low-frequency bands. Thus there is a need for filter pairs at both the analysis and synthesis stages. This paper aims in tutorial form to introduce the DWT, to illustrate its link with filters and filterbanks and to illustrate how it may be used as part of an image coding algorithm. It concludes with a look at the qualitative differences between images coded using JPEG2000 and those coded using the existing JPEG standard.

Color Image Watermarking Algorithm Based on DWT-SVD

Abstract: A novel watermarking scheme of embedding a scrambling watermark into the green component of the color image based on DWT-SVD is proposed. The green component is decomposed for LLn, HLn, LHn, HHn with DWT at the Nth levels. For each subband, adopt different methods to complete the watermark embedding. For the part LLn, imbed pseudo-random after spreading according to the energy. Decompose the three wavelet matrix coefficients LHn, HLn, HHn with SVD. Add the SVD of the scrambled watermarking and the SVD of the wavelet coefficients, and then the imbedding course is accomplished. The retrieving watermark algorithm and the blind detecting algorithm both are designed according to the embedding scheme. The experiment indicates that the watermark is robust to JPEG compression, cropping, Gaussian noise, median filter and resize.

Illumination-tolerant face verification of low-bit-rate JPEG2000 wavelet images with advanced correlation filters for handheld devices

Abstract: Face recognition on mobile devices, such as personal digital assistants and cell phones, is a big challenge owing to the limited computational resources available to run verifications on the devices themselves. One approach is to transmit the captured face images by use of the cell-phone connection and to run the verification on a remote station. However, owing to limitations in communication bandwidth, it may be necessary to transmit a compressed version of the image. We propose using the image compression standard JPEG2000, which is a wavelet-based compression engine used to compress the face images to low bit rates suitable for transmission over low-bandwidth communication channels. At the receiver end, the face images are reconstructed with a JPEG2000 decoder and are fed into the verification engine. We explore how advanced correlation filters, such as the minimum average correlation energy filter [ Appl. Opt.26, 3633 ( 1987)] and its variants, perform by using face images captured under different illumination conditions and encoded with different bit rates under the JPEG2000 wavelet-encoding standard. We evaluate the performance of these filters by using illumination variations from the Carnegie Mellon University’s Pose, Illumination, and Expression (PIE) face database. We also demonstrate the tolerance of these filters to noisy versions of images with illumination variations.

Continuous dynamic Indian Sign Language gesture recognition with invariant backgrounds

Abstract: Hand gestures are a strong medium of communication for hearing impaired society It is helpful for establishing interaction between human and computer In this work we proposed a continuous Indian Sign Language (ISL) gesture recognition system where single hand or both the hands have been used for performing gestures Our proposed method is also invariant against various backgrounds Tracking useful frames of gestures from continuous frame, frame overlapping method has been applied Here we extract those frames which contains maximum information This is helpful for speedup the recognition process After that discrete wavelet transform (DWT) is applied for extracting features of an image frame and finally hidden markov model (HMM) is used for testing probe gestures Experiments are performed on our own continuous ISL dataset which is created using canon EOS camera in Robotics and Artificial Intelligence laboratory (IIIT-A) From experimental results we have found that our proposed method works on various backgrounds like colored background, a background containing multiple objects etc also this framework provides vary less time complexity as well as space complexity

Image quality comparison between JPEG and JPEG2000. I. Psychophysical investigation

Abstract: The original JPEG compression standard is efficient at low to medium levels of compression with relatively low levels of loss in visual image quality and has found widespread use in the imaging industry. Excessive compression using JPEG however, results in well-known artifacts such as "blocking" and "ringing," and the variation in image quality as a result of differing scene content is well documented. JPEG 2000 has been developed to improve on JPEG in terms of functionality and image quality at lower bit rates. One of the more fundamental changes is the use of a discrete wavelet transform instead of a discrete cosine transform, which provides several advantages both in terms of the way in which the image is encoded and overall image quality. This study involves a comparison of subjective image quality between JPEG and JPEG 2000 to establish whether JPEG 2000 does indeed demonstrate significant improvements in visual quality. A particular focus of this work is the inherent scene dependency of the two algorithms and their influence on subjective image quality results. Further work on the characterization of scene content is carried out in a connected study [S. Triantaphillidou, E. Allen, and R. E. Jacobson, "Image quality comparison between JPEG and JPEG2000. II. Scene dependency, scene analysis, and classification"

Local B-Spline Multiresolution with Example in Iris Synthesis and Volumetric Rendering.

Abstract: Multiresolution has been extensively used in many areas of computer science, including biometrics. We introduce local multiresolution filters for quadratic and cubic B-splines that satisfy the first and the second level of smoothness respectively. For constructing these filters, we use a reverse subdivision method. We also show how to use and extend these filters for tensor-product surfaces, and 2D/3D images. For some types of data, such as curves and surfaces, boundary interpolation is strongly desired. To maintain this condition, we introduce extraordinary filters for boundaries. For images and other cases in which interpolating the boundaries is not required or even desired, we need a particular arrangement to be able to apply regular filters. As a solution, we propose a technique based on symmetric extension. Practical issues for efficient implementation of multiresolution are discussed. Finally, we discuss some example applications in biometrics, including iris synthesis and volumetric data visualization.