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HYBRID wavelet - DCT INTRA PREDICTION FOR H.264/AVC INTERACTIVE ENCODER 2

HYBRID WAVELET - DCT INTRA PREDICTION FOR H.264/AVC INTERACT...

引用

2nd IEEE China Summit / International conference on signal and Information processing (IEEE ChinaSIP)

作者： Elarabi, T. Sammoud, A. Abdelgawad, A. Li, X. Bayoumi, M. UL Lafayette CACS Lafayette LA 70504 USA Cent Michigan Univ Mt Pleasant MI USA

ISBN: (纸本)9781479954032

With the growing usage of mobile video applications and Internet based video services;techniques and algorithms of the current video compression standards face new challenging demands for lower bit-rate and faster processing speed. H.264/AVC video compression standard is widely used and provides state of the art video compression solution, but still needs to address the challenges of high bit-rate and required processing power. In this paper, a low bit-rate compression algorithm is proposed, which introduces a novel approach that use both DCT (Discrete Cosine Transform) and DWT (Discrete wavelet Transform) for enhancing the Intra-Prediction phase of H.264/AVC standard. The proposed Hybrid wavelet-DCT (HW-DCT) algorithm modifies the FSF (Full Search Free) algorithm;by adding wavelet-based transformation prior to the Intra-prediction process. The HW-DCT algorithm adds up the advantages of wavelet based compression technique to the speed of the FSF algorithm and creates an Intra-prediction algorithm that guarantees 51% lower bit-rate while maintaining similar visual quality and Peak signal to Noise Ratio (PSNR) of the original H. 264/AVC Intra-prediction algorithm. The JM 18.2 Reference software implementation results have validated the effectiveness of our proposed algorithm and shown a significant improvements in both run-time and bit-rate.

关键词： H.264/AVC Intra Prediction wavelet Transformation image Compression

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Double-Density Dual-Tree wavelet-based Polarimetry Analysis

Double-Density Dual-Tree Wavelet-based Polarimetry Analysis

引用

IEEE National Aerospace and Electronics conference (NAECON)

作者： Harrity, Kyle Ezekiel, Soundararajan Bubalo, Adnan Blasch, Erik Alford, Mark Indiana Univ Penn Indiana PA 15701 USA US Air Force Res Lab Rome NY 13441 USA

ISBN: (纸本)9781479946891

For the past two decades, the Discrete wavelet Transformation (DWT) has been successfully applied to many fields. For image processing applications, the DWT can produce non-redundant representations of an input image with greater performance than other wavelet methods. Further, the DWT provides a better spatial and spectral localization of image representation, capable of revealing smaller changes, trends, and breakdown points that classical methods often miss. However, the DWT has its own limitations and disadvantages such as lack of shift invariance. That is, if the input signal or image is shifted, then the wavelet coefficients will exacerbate that shift. The DWT also lacks the ability to represent directional cases. The Double Density Dual-Tree Discrete wavelet Transformation (D3TDWT) is a relatively new and enhanced version of the DWT with two scaling functions and four distinct wavelets designed in such a way that one pair of wavelets is offset with another pair so that the first pair lies in between the second. In this paper, we propose a D3TDWT polarimetry analysis method to analyze Long Wave Infrared (LWIR) polarimetry imagery to discriminate objects such as people and vehicles from background clutter. The D3TDWT method can be applied to a wide range of applications such as change detection, shape extraction, target recognition, and simultaneous tracking and identification.

关键词： Polarimetry Discrete wavelet Transform Energy Stokes Long Wave Infrared Double Density Dual Tree

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3D Dual-Tree Discrete wavelet Transform Based Multiple Description Video Coding 11

3D Dual-Tree Discrete Wavelet Transform Based Multiple Descr...

引用

11th International conference on signal processing and Multimedia applications (SIGMAP) is part of 11th International Joint conference on E-Business and Telecommunications (ICETE)

作者： Chen, Jing Cai, Canhui Li, Li Huaqiao Univ Sch Informat Sci & Engn Xiamen Peoples R China Xiamen Univ Sch Informat Sci & Engn Xiamen Peoples R China

ISBN: (纸本)9789898565969

A 3D dual-tree discrete wavelet transform (DT-DWT) based multiple description video coding algorithm is proposed to combat the transmitting error or packet loss due to Internet or wireless network channel failure. Each description of the proposed multiple description coding scheme consists of a base layer and an enhancement layer. First, the input image sequence is encoded by a standard H.264 encoder in low bit rate to form the base layer, which is then duplicated to each description. Second, the difference between the reconstructed base layer and the input image sequence is encoded by a 3D dual-tree wavelet encoder to produce four coefficient trees. After noise-shaping, these four trees are partitioned into two groups, individually forming enhancement layers of two descriptions. Since the 3D DT-DWT equips 28 directional subbands, the enhancement layer can be coded without motion estimation. The plenty of directional selectivity of DT-DWT solves the mismatch problem and improves the coding efficiency. If all descriptions are available in the receiver, a high quality video can be reconstructed by a central decoder. If only one description is received, a side decoder can be used to reconstruct the source with acceptable quality. Simulation results have shown that the quality of reconstructed video by the proposed algorithm is superior to that by the state-of-the-art multiple description video coding methods.

关键词： Multiple Description Coding Video Coding Dual-Tree Discrete wavelet Transform Layer Coding

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image Denoising using wavelet Transform and Wiener Filter based on Log Energy Distribution over Poisson-Gaussian Noise Model 5

Image Denoising using Wavelet Transform and Wiener Filter ba...

引用

5th IEEE International conference on Computational Intelligence and Computing Research (IEEE ICCIC)

作者： Boyat, Ajay Kumar Joshi, Brijendra Kumar MITM Dept ECE Indore Madhya Pradesh India MHOW Mil Coll Tele Commun Engn Dept ECE Indore Madhya Pradesh India

ISBN: (纸本)9781479939756

Generally Gaussian noise model is used in image processing applications due to its presence in electronic circuitry used in image acquisition devices like Charge Coupled Device (CCD) cameras. Off let due to discrete nature of electromagnetic radiation in image acquisition process, due to photon noise that follows poison distribution is also exist with Gaussian noise. In this paper we present an algorithm based on wavelet transform and wiener filter using log energy distribution to denoised digital images corrupted by Poisson-Gaussian noise. Our results clearly demonstrate the robustness of the algorithm over a large range of variance. We have used peak signal to noise ratio (PSNR) for comparison based on filter outlet.

关键词： Poisson noise Guassian noise Haar wavelet Wiener filter Log energies PSNR

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Illumination invariant pattern recognition using fringe-adjusted joint transform correlator and monogenic signal

Illumination invariant pattern recognition using fringe-adju...

引用

conference on image processing - Machine Vision applications vii

作者： Sidike, Paheding Asari, Vijayan K. Alam, Mohammad S. Univ Dayton Dept Elect & Comp Engn Dayton OH 45469 USA Univ S Alabama Dept Elect & Comp Engn Mobile AL 36688 USA

ISBN: (纸本)9780819499417

The joint transform correlator (JTC) technique has shown attractive performance for real-time pattern recognition applications. Among the various JTC techniques proposed in the literature, the fringe-adjusted JTC (FJTC) yields remarkable promise for object recognition, and it has been shown that the FJTC produces a better correlation output than alternate JTCs under varying illumination conditions of the input scene;however, it has been found that the FJTC is not illumination invariant. Therefore, to alleviate this drawback of the FJTC, an illumination-invariant FJTC, based on combination of the fringe-adjusted filter (FAF) and the monogenic signal, is presented. The performance of the FJTC and the proposed local phase based FJTC technique in unknown input-image with varying illumination is investigated and compared. The proposed detection algorithm makes use of the monogenic signal from a two dimensional object region to extract the local phase information for assisting the FJTC robust to illumination effects. Experimental results show that by utilizing the monogenic phase information enables the FAF-based JTC to produce sharper correlation peaks and higher peak-to-clutter ratio compared to alternate JTCs. The proposed technique may be used as a real-time region-of-interest identifier in wide-area surveillance for automatic object recognition when the target under very dark or bright condition that beyond human vision.

关键词： Pattern recognition joint transform correlation fringe-adjusted filter monogenic signal illumination invariant

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image reconstruction from phase hologram obtained by using single phase information

Image reconstruction from phase hologram obtained by using s...

引用

2014 22nd signal processing and Communications applications conference, SIU 2014

作者： Kaya, Gulhan Ustabas Sarac, Zehra Tayyar, Duygu Onal Bolumu, Fizik Elektrik Ve Elektronik Mühendisliǧi Bölümü Bülent Ecevit Üniversitesi Zonguldak Turkey GYTE Kocaeli Turkey

ISBN: (纸本)9781479948741

In this study, it is aimed to obtain the real time image of the object, whose off-axis hologram recording is saved on CCD camera, from digital phase hologram. For creating the phase hologram, the phase information of the hologram recording on CCD camera is obtained. When the phase information is obtained, the Fourier transform algorithm and continuous wavelet transform methods are used. Finally, the using methods in this study are compared in terms of obtaining real time image having a high image quality and minimum power loss. © 2014 IEEE.

关键词： CCD cameras

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wavelet Based SAR Data Denoising and Analysis

Wavelet Based SAR Data Denoising and Analysis

引用

4th IEEE International Advance Computing conference (IACC)

作者： Misra, Arundhati Kartikeyan, B. Garg, S. SAC ISRO EPSA ATDG Ahmadabad Gujarat India ISRO IAQD SIPA SAC Ahmadabad Gujarat India Nirma Univ Dept Comp Sci Ahmadabad Gujarat India

ISBN: (纸本)9781479925711

Real world signals are afflicted by noise, be it the communication signals or the remote sensor signals including the medical imaging sensors or surveillance sensors. In the case of signals from SAR(Synthetic Aperture Radar) sensor from remote sensing platforms, or USG or MRI from medical images, the noise is multiplicative. The coherent nature of the signal processing involved in the data generation for the latter, gives rise to a g rainy kind of signal dependent noise called speckle. Speckle noise affects the radiometric quality of the image and makes data interpretation and analysis difficult. Since the utility of any data depends on the accuracy of the data both in terms of geometry and radiometry, denoising becomes mandatory for image analysis applications. The common problem with most of these denoising filters is that they blur the images while reducing the noise. The challenge thus, lies in cleaning the image without sacrificing the geometric resolution. wavelet based filtering techniques show promising results in this regard. In this paper the results and analysis of performing filtering on high resolution SAR data, using different mother wavelets of Daubechie's using soft thresholding technique, are presented.

关键词： SAR speckle denoise wavelets ENE S/MSE etc

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Watermarking signal fusion in multimodal biometrics 1

Watermarking signal fusion in multimodal biometrics

引用

2014 1st International image processing, applications and Systems conference, IPAS 2014

作者： Haddada, Lamia Rzouga Dorizzi, Bernadette Essoukri Ben Amara, Najoua Research Unit of Advanced Systems in Electrical Engineering National Engineering School of Sousse Tunisia Institut Mines-Telecom Telecom Sud Paris Laboratoire Samovar France

ISBN: (纸本)9781479970698

In this paper, we propose a new approach based on watermarking for fusing biometric modalities. The main idea of the proposed approach is to use the watermark both for security purpose and as an additional information related to the person, therefore increasing the personal data used for verification. The host image of the face is watermarked in the multi-resolution space by the palmprint using a watermarking technique based on wavelet packet decomposition. For the verification stage, the characterization of the watermarked face is provided by Gabor filters while classification is performed by SVMs. The experimental results show that this technique ensures a significant performance improvement in both identity verification and biometric security over the use of a single system. © 2014 IEEE.

关键词： Gabor filters

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A novel encryption algorithm for quantum images based on quantum wavelet transform and diffusion 1

A novel encryption algorithm for quantum images based on qua...

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1st Euro-China conference on Intelligent Data Analysis and applications, ECC 2014

作者： Wang, Shen Song, Xianhua Niu, Xiamu School of Computer Science and Technology Harbin Institute of Technology Harbin China

ISBN: (纸本)9783319077727

In this paper, a novel quantum encryption scheme for quantum images based on quantum wavelet transform (QWT) and double diffusions is proposed. Firstly, diffusion operation applied on the input quantum image, and then QWT worked on the new quantum image to transform this image to the frequency domain. and following the diffusion operation is implemented on the QWT transformed quantum image. finally ,inverse QWT are *** encryption keys are generated by a sensitive chaotic logistic map, which guarantee the security of the scheme. at the same time,we designed the corresponding quantum circuits to demonstrates that the reasonable of the proposed scheme. © 2014 Springer International Publishing Switzerland. All rights reserved.

关键词： wavelet transforms

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No-reference Blur Metric using Double-Density and Dual-Tree Two-Dimensional wavelet Transformation

No-reference Blur Metric using Double-Density and Dual-Tree ...

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IEEE National Aerospace and Electronics conference (NAECON)

作者： Ezekiel, Soundararajan Harrity, Kyle Blasch, Erik Bubalo, Adnan Indiana Univ Penn Indiana PA 15701 USA US Air Force Res Lab Rome NY 13441 USA

ISBN: (纸本)9781479946891

Over the past decade the digital camera has become widely available in many devices such as cell phones, computers, etc. Therefore, the perceptual quality of digital images is an important and necessary requirement to evaluate digital images. To improve the quality of images captured with camera, we must identify and measure the artifacts that cause blur within the images. Blur is mainly caused by pixel intensity due to multiple sources. The most common types of blurs are known as object motion, defocus, and camera motion. In the last two decades, the discrete wavelet transformation (DWT) has become a cutting-edge technology in the signal and image processing field for such applications as denoising. The disadvantage of the DWT is that it is not able to directly observe blur coefficients. In this paper, we propose a novel framework for a blur metric for an image. Our approach is based on the double-density dual tree two dimensional wavelet transformations (D3TDWT) which simultaneously processes the properties of both the double-density DWT and dual tree DWT. We also utilize gradient to evaluate blurring artifacts and measure the image quality.

关键词： No-Reference Double-Density Double-Tree Discrete wavelet Transformation Blur image Quality Assessment

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