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A GPGPU accelerated compressed sensing with tight wavelet frame transform technique for MR imaging reconstruction

A GPGPU accelerated compressed sensing with tight wavelet fr...

引用

IEEE International Workshop on Imaging Systems and Techniques (IST)

作者： B. Hu X. Ma M. Joyce Paul. Glover Buhary. Naleem Department 0 f Engineering Lancaster University Lancaster UK Sir Peter Mansfield Magnetic Resonance Centre University of Nottingham Nottingham UK

High resolution Magnetic Resonance Imaging (MRI) requires long acquisition time to obtain the fully sampled k-space data for image reconstruction. Compressed Sensing (CS) theory has recently been utilized to accelerate the image reconstruction speed by sparsely sampling the k-space. In this work, the CS framework was combined with the Tight wavelet Frame (TWF) transform to further enhance edges/boundaries of MR images and reduce their noise levels. Because the TWF coefficients at finer scale correspond to important image boundary features, the proposed algorithm is able to effectively enhance the signal to noise ratio of MR images without blurring their edges or create artifacts. The resulting constrained minimization problem is then solved iteratively and requires extensive computational resources. To accelerate the reconstruction for real-time medical image processing purpose, the algorithm is implemented on the General Purpose Graphic processing Units (GPGPU). The effects of various factors, including the register counts and block size, on the GPU occupancy have been investigated to tune the hardware for the optimum performance. The proposed algorithm demonstrates great potential to accelerate the MR imaging acquisition by 8-fold without noticeable artifacts. Comparisons with other two l 1 minimization methods with traditional wavelet transforms further confirm the competitiveness of the proposed algorithm. Moreover, a speedup of 45 times was achieved by the GPGPU implementation compared with the CPU version, and therefore making this algorithm suitable for applications in a clinical MRI setting.

关键词： image resolution Acceleration image reconstruction Imaging signal resolution Ear

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Successive bit-plane rate allocation technique for JPEG2000 image coding

Successive bit-plane rate allocation technique for JPEG2000 ...

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International conference on Acoustics, Speech, and signal processing (ICASSP)

作者： Y.M. Yeung O.C. An A. Chang Department of Electrical and Electronic Engineering The Hong Kong University of Science and Technology Hong Kong China Hong Kong University of Science and Technology Kowloon HK Dept. of Electr. & Electron. Eng. Hong Kong Univ. of Sci. & Technol. China Department of Electrical and Electronic Engineering The Hong Kong University of Science and Technology

A novel rate control scheme using successive bit-plane rate allocation (SBRA) is proposed for JPEG2000 image coding. By using the current rate-distortion information only, the proposed method can achieve a quality close to the post-compression rate-distortion (PCRD) optimization scheme adopted in JPEG2000. The proposed scheme can efficiently reduce both the computational cost and working memory size of the entropy coding process up to about 90%, in the case of 0.25bpp (1/32) compression. Without using the future rate-distortion information, the sequential property of the proposed method is highly suitable for real-time (or low delay) applications and implementation.

关键词： image coding Rate-distortion Discrete wavelet transforms Bit rate Delay Spatial resolution image resolution Bandwidth image quality Discrete cosine transforms

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Biometric Cryptosystem Scheme for Internet of Things using Fuzzy Commitment principle

Biometric Cryptosystem Scheme for Internet of Things using F...

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International conference on signal, image, Vision and their applications (SIVA )

作者： Atef Bentahar Abdallah Meraoumia Hakim Bendjenna Salim Chitroub Abdelhakim Zeroual LAboratory of Mathematics Informatics and Systems (LAMIS) University of Larbi Tebessi Tebessa ALGERIA LISIC Laboratory Telecommunication Department USTHB BP. 32 El-Alia Bab-Ezzouar Algiers ALGERIA

ISBN: (纸本)9781538671214;9781538671207

Recently, the ensuring security by biometric authentication/identification presents a big challenge for network designers. This precious biometric information have to be itself protected against fraudulent uses, especially during the remote authentication and data exchange in wireless mesh networks such as the Internet of Things (IoT). This paper presents a securing biometric cryptosystem for IoT based on fuzzy commitment principle which is suitable of the connected things due to their low processing and memorization capacity. Our scheme, which is based on fingerprint modalities, can be decomposed into two parts. Firstly, at the sender side, a biometric feature vector is extracted using DWT technique and then the data is encrypted in order to transmit via internet. Secondly, at the receiver side, an authentication protocol was used to authenticate the things and decrypt the received data. The obtained results, using a popular fingerprint dataset, show that the proposed scheme is more secure, fast and points at increased authentication accuracy.

关键词： Cryptography Fingerprint recognition Authentication Feature extraction Discrete wavelet transforms Internet of Things

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A comprehensive approach for texture classification

A comprehensive approach for texture classification

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International Symposium on signal processing and Its applications (ISSPA)

作者： P. Ammi Reddy P. S. R. Chandra Murty E. Sreenivasa Reddy Jawaharlal Nehru Technological University Kakinada A.P. India Department of Computer Science and Engineering Vasireddy Venkatadri Institute of Technology Guntur A.P. India

Classification of textures based on wavelet pattern analysis is one of the most effective methods in texture classification. However using all frequency sub-bands in decomposition for classification may increase time complexity of classification algorithms. To reduce the time complexity, sub-bands with high energy and entropy are selected for classification. Fractal dimension can be used to select such significant sub-bands for decomposition at each level. Further statistical features of these significant sub-bands are given to modified K-NN classifier for classification. This paper describes texture classification using sub-bands of wavelets based on fractal dimensions and their results are compared with the results of texture classification using conventional features and also with different classifiers. Success rate is very high and time complexity is also reduced to the order of O(n).

关键词： Wool Weaving image recognition Computers

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Application of Distributed Arithmetic in image and ECG signal processing

Application of Distributed Arithmetic in Image and ECG Signa...

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International conference on Current Trends in Computer, Electrical, Electronics and Communication

作者： Anu Mary Sunny Naveen Jacob Dept. of Electronics and Communication Engineering Viswajyothi College of Engineering & Technology Vazhakulam Kerala India

ISBN: (纸本)9781538632444

The core of many DSP applications involve convolution which was previously implemented by Multiply and Accumulate operations or MAC. It requires a number of multipliers and accumulators. The use of multipliers and accumulators result in faster execution but it also results in an increase in cost. Also the number of multipliers and adders are limited. Hence a new technique known as Distributed Arithmetic (DA) was proposed. It is basically a multiplier-less concept utilizing Lookup Table (LUT). It is used when one of the operand is fixed. The input enters into a serial register which is used to access the LUT. To get the address from the LUT we consider the bit positions and get the values of inputs by that bit position. The output from the lookup table is shifted accordingly and the shifted results are added together to form the final result. Hence it basically involves accessing the lookup table, shift and add operation. After implementing the DA logic and comparing it with the convolution scheme, we apply this concept in Discrete wavelet Transform (DWT) of an image and ECG signal by using Haar filter coefficient.

关键词： Distributed Arithmetic Discrete wavelet Transform ECG signal

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A DSP for DCT-based and wavelet-based video codecs for consumer applications

A DSP for DCT-based and wavelet-based video codecs for consu...

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Custom Integrated Circuits conference (CICC)

作者： K. Okamoto T. Jinbo T. Araki Y. Iizuka H. Nakajima M. Takahata H. Inoue S. Kurohmaru T. Yonezawa K. Aono Semiconductor Research Center Matsushita Elecrric Indusrrial Company Limited Osaka Japan LSI Development Center Matsushita Electronics Corporation Osaka Japan Corporate Research Division Matsushita Elecrric Indusrrial Company Limited Osaka Japan

We have developed a video DSP which performs real-time encoding and decoding for DCT-based algorithms, such as ITU-T H.261, and wavelet-based subband encoding algorithms. This LSI is suitable for consumer applications as it was implemented using 0.5 /spl mu/m-CMOS process technology to realize compactness (1 million transistors on 65 mm/sup 2/) and low power(560 mW). It features a processing unit which performs wavelet filtering at high speeds, a compact DCT circuit, and a fast, flexible DRAM interface for low-cost systems. At 40 MHz, a single chip is capable of processing QCIF size pictures at a rate of over 15 frames/second.

关键词： Digital signal processing Band pass filters Large scale integration Discrete cosine transforms image coding Convolution Electronics industry Encoding Decoding Application software

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Hybrid model for preserving brightness over the digital image processing

Hybrid model for preserving brightness over the digital imag...

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International conference on Computer and Communication Technology (ICCCT)

作者： Vaishali Ahirwar Himanshu Yadav Anurag Jain Department of Computer Science & Engineering RITS Bhopal

Digital image processing is versatile research in this era. Many researchers implement different types of organizations like image restoration, image enhancement, color image processing, image segmentation etc. image enhancement technique is among the simplest and most appealing area of digital image processing. Enhancement techniques like brightness preservation, contrast enhancement highlight certain features means depend which part of the image want to be enhance some application some input image including noise, reduction or removal of noise is also form of image enhancement. Brightness preservation has enhanced visual quality of digital image so that the limitation contained in these images is used for various applications in a better way. A very popular technique for image enhancement is histogram equalization (HE) and curvelet transformation. HE technique is commonly employed for image enhancement because of its simplicity and comparatively better performance on almost all types of images. Another widely used technique is curvelet transformation. This technique is identified and separate bright regions of image but more error rate and low peak signal to noise ratio(PSNR), result of this technique is brightness preservation level is low and output image is gray. This paper design a hybrid model through discrete cosine transformation, discrete wavelet transformation and combine output of both techniques with image fusion. Proposed algorithm enhanced features and removal noise by decomposition of image using DWT and discrete cosine transformation, adaptive histogram equalization is very important part in this algorithm for smooth image. The tested results of different images are comparing with previous method, generating result with different parameters; less mean square error and high PSNR for improve the quality of an image. This paper presents a hybrid model used various parameter for enhance images like satellite images, medical images etc.

关键词： Discrete wavelet transforms Brightness Histograms image fusion PSNR Discrete cosine transforms

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Activity detection in unknown noise environment

Activity detection in unknown noise environment

引用

International conference on Acoustics, Speech, and signal processing (ICASSP)

作者： E. Fishler H. Messer Department of Electrical Engineering Systems Tel-Aviv University Tel-Aviv Israel

In many applications there exists an array of cells (or bins), each containing either an activity (signal) plus noise, or noise only. A common problem is to identify the active bins, assuming that the noise level in the array is unknown. In this paper we present a novel approach for solving this problem. The approach is based on two steps. In the first, we estimate the noise level and in the second we perform a sequential test to decide, for each bin, whether it is active or not. We show that the proposed algorithm collapses to well known special cases. The performance of the proposed algorithm is analyzed analytically and is demonstrated via simulation results.

关键词： Working environment noise Noise measurement Noise level wavelet transforms Performance analysis Additive noise image denoising Performance evaluation Sequential analysis Analytical models

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Medical image Compression Using Ripplet Transform

Medical Image Compression Using Ripplet Transform

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International conference on Intelligent Computing applications (ICICA)

作者： C. Dhaarani D. Venugopal A. Sivanantha Raja Dept of ECE K.L.N College of Information Technology Madurai Tamilnadu India Dept of ECE A. C. College of Engineering & Technology Karaikudi Tamilnadu India

Now-a-days the medical image compression plays a major role in the image processing. Even though the technology is improvised but still it needs the storage space and efficient bandwidth utilization. This paper presents the compression of grey scale medical images. The proposed method uses a new transform called Ripplet Transform, a higher dimensional generalization of the curvelet transform used to represent the images or two dimensional signals at different scales and different directions and Huffman algorithm to encode significant coefficients. The main goal of this method is to improve the compression ratio and to minimize the mean square error. From the experimental results obtained it is proved that the compression ratio and the peak to signal noise ratio is achieved high for various Medical images.

关键词： image coding Biomedical imaging PSNR wavelet transforms Huffman coding Magnetic resonance imaging

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Digital image watermarking scheme based on histogram in DWT domain

Digital image watermarking scheme based on histogram in DWT ...

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International conference on Digital Content, Multimedia Technology and its applications (IDC)

作者： Xiao-Chen Yuan Chi-Man Pun Department of Computer and Information Science University of Macau Macao China

A robust and geometric invariant digital watermarking scheme for gray-level images is proposed in this paper. The scheme carries out watermark embedding and extraction based on histogram in DWT domain. For watermark embedding, the original image is decomposed into the approximation and details sub-bands. Pixels of the approximation sub-band are grouped into m blocks, each of which has the same number of intensity-levels, thus the block histogram is generated; with the block histogram, pixels are moved to form a specific pattern in the intensity-level histogram distribution, indicating the watermark. For watermark extraction, the watermarked image is decomposed into the approximation and details sub-bands; then the pixels in the approximation sub-band are grouped into blocks in the similar manner. According to the histogram distribution in each block, the watermark is extracted. Experimental results show that the proposed scheme is highly robust against JPEG compression, geometric attacks and some common signal processing.

关键词： image coding Discrete wavelet transforms Fractals Robustness Cryptography Pixel Transform coding

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