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Region of Interest Extraction Based on Saliency Detection and Contrast Analysis for Remote Sensing images 22

Region of Interest Extraction Based on Saliency Detection an...

引用

conference on image and signal processing for Remote Sensing XXII

作者： Lv, Jing Zhang, Libao Wang, Shuang North China Elect Power Univ Elect & Elect Engn Sch Beijing 102206 Peoples R China Beijing Normal Univ Coll Informat Sci & Technol 19 Xinjiekouwai Rd Beijing 100875 Peoples R China

ISBN: (数字)9781510604131

ISBN: (纸本)9781510604124;9781510604131

Region of Interest (ROI) extraction is an important component in remote sensing images processing, which is useful for further practical applications such as image compression, image fusion, image segmentation and image registration. Traditional ROI extraction methods are usually prior knowledge-based and depend on a global searching solution which are time consuming and computational complex. Saliency detection which is widely used for ROI extraction from natural scene images in these years can effectively solve the problem of high computation complexity in ROI extraction for remote sensing images as well as retain accuracy. In this paper, a new computational model is proposed to improve the accuracy of ROI extraction in remote sensing images. Considering the characteristics of remote sensing images, we first use lifting wavelet transform based on adaptive direction evaluation (ADE) to obtain multi-scale orientation contrast feature map (MF). Secondly, the features of color are exploited using the information content analysis to provide a color information map (CIM). Thirdly, feature fusion is used to integrate multi-scale orientation contrast features and color information for generating a saliency map. Finally, an adaptive threshold segmentation algorithm is employed to obtain the ROI. Compared with existing models, our method can not only effectively extract detail of the ROIs, but also effectively remove mistaken detection of the inner parts of the ROIs.

关键词： Remote sensing image processing region of interest extraction saliency detection orientation contrast feature color information map

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ECCOMAS Thematic conference on Computational Vision and Medical image processing, Vipimage 2015

ECCOMAS Thematic Conference on Computational Vision and Medi...

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5th Eccomas Thematic conference on Computational Vision and Medical image processing, Vipimage 2015

ISBN: (纸本)9781138029262

The proceedings contain 55 papers. The special focus in this conference is on Computational Vision and Medical image processing. The topics include: Medical image segmentation using object shape models;primal-dual method for continuous max-flow approaches;image restoration using variational approaches;applications to simulation, training, surgical planning and interventional guidance;the fast method of creating high dynamic range image for fluorescent microscopy applications;automatic cheek detection in digital images;a variational model for image fusion with simultaneous cartoon and texture decomposition;image contrast enhancement using split bregman method;extraction of spectral drowsy component from the resting electroencephalographic signal for quick, objective and direct testing of sleepiness in absolute terms;the illusion of a blackbody at the human ear and the human temperature measurement;video-based Turkish sign language recognition systems;a nonsmooth nonconvex sparsity-promoting variational approach for deblurring images corrupted by impulse noise;classification-based blood vessel segmentation in retinal images;line extraction via phase congruency with a novel adaptive scale selection for poisson noisy images;diagnosis of human intestinal parasites by deep learning;texture-energy features for microaneurysms detection;no-reference wavelet based retinal image quality assessment;vessel segmentation of retinal images with fuzzy morphology;microcalcification segmentation in full field digital mammography;unsupervised delineation of the vessel tree in retinal fundus images;a registration algorithm for microscopy images of the capillary bed;bilateral filtering based biomedical image colorization and comparison of the internal structures of bones by microtomography.

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An Intelligent System to Classify Epileptic and Non-Epileptic EEG signals 12

An Intelligent System to Classify Epileptic and Non-Epilepti...

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12th International conference on signal-image Technology and Internet-Based Systems (SITIS)

作者： Qazi, Emad-ul-Haq Hussain, Muhammad Aboalsamh, Hatim Abdul, Wadood Bamatraf, Saeed Ullah, Ihsan King Saud Univ Coll Comp & Informat Sci Dept Comp Sci Riyadh Saudi Arabia King Saud Univ Coll Comp & Informat Sci Dept Comp Engn Riyadh Saudi Arabia Univ Napoli Parthenope Dept Sci & Technol CVPR Lab Naples Italy

ISBN: (纸本)9781509056989

Epilepsy is a neurological disorder disease that affects more than 55 million people in the world. In this paper, we have proposed an efficient intelligent pattern recognition system for the classification of epileptic and non-epileptic electroencephalogram (EEG) signals. For this purpose, we used state-of-the-art machine learning technique, i.e., SVM (support vector machines) to classify epileptic and non-epileptic signals. Two (02) different classes of signals are used in this study, i.e., non-epileptic with open eyes and epileptic in seizure condition. One hundred (100) subjects from each class were employed for extraction of discriminatory features and classification purpose. After pre-processing of EEG signals, we use discrete wavelet transform (DWT) to decompose signals upto level 5. Then various features, i.e., energy, entropy and standard deviation are extracted from wavelet bands. Next, we use these features in the classification of signals. We achieved the classification accuracy of 100 % at delta band (0 to 3 Hz) and theta band (3 to 6 Hz). The comparisons with the previous studies show the significance of this system, which can be utilized in real-time as well as in offline clinical applications.

关键词： Electroencephalogram (EEG) Discrete wavelet transform (DWT) Support Vector Machine (SVM) Epileptic Non-Epileptic

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Digital watermarking scheme for image authentication

Digital watermarking scheme for image authentication

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International conference on Communication and signal processing

作者： Lakshmi Priya, C. V. Nelwin Raj, N. R. SreeChitraThirunal College of Engineering Thiruvananthapuram India

Digital image watermarking process is definite as to insert information of digital into digital signal. This is an efficient solution to avoid illegal copying of information from multimedia networks. Many watermarking algorithms have been developed and each of them has its own individuality because of its variety of applications. A new algorithm able to solve most of the practical issues of watermarking is designed. Watermarking alone is not sufficient to prevent the unauthorized manipulations of data unless a proper protection protocol is established. An efficient watermarking algorithm should satisfy an optimal trade-off between three factors such the capacity, robustness and imperceptibility. The proposed algorithm uses the advantage of singular value decomposition (SVD), discrete wavelet transform (DWT) and homomorphic filtering. Finally, the efficiency of the result is evaluated using various quality measurements and the watermarked image is encrypted to increase the security level.

关键词： Digital water marking DWT SVD Homomorphic filtering Encryption

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Enhancing Phase Retrieval Speed for Real-time Interferometer and ESPI by Two-dimensional Continuous wavelet Transform 30

Enhancing Phase Retrieval Speed for Real-time Interferometer...

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SPIE Practical Holography XXX conference

作者： Wang, Chun-Hsiung Hsu, Kuan-Yu Lee, Chih-Kung Natl Taiwan Univ Inst Appl Mech Taipei Taiwan Natl Taiwan Univ Dept Engn Sci & Ocean Engn Taipei Taiwan

ISBN: (纸本)9781510600065

A real-time three-dimensional surface profile metrology system was implemented by integrating Fourier Transform (FT) based algorithms to convert interference intensity fringes to wrapped frequency phase maps and then to unwrapped phase maps. The revival of this field can find its roots in recognizing the development of high-resolution highspeed CCD/CMOS over the years. Two-dimensional Continuous wavelet Transform (2D-CWT), which possesses the ability to construct daughter wavelets of good time and frequency localization according to different fringes conditions from a characteristic mother wavelet, was implemented with an attempt to reduce redundant fitting process of ordinary Short Time Fourier Transform (STFT), also known as Windowed Fourier Transform (WFT), and therefore to accelerate the FT-related algorithms needed. Implemented with the efficient wavelet construction process by using 2D-CWT, Electronic Speckle Pattern Interferometer (ESPI) was adopted to take advantage of this new process. Different from using several phase shifting steps before to solve the direction ambiguity, which takes time to capture multiple intensity maps during measurement, the phase maps needed were retrieved from a single frame interference fringes. It is to be noted that this one-image interference fringe was captured by having a pre-introduced spatial carrier frequency embedded within the experimental setup so as to remove the directional ambiguity. 2D-CWT dealing with different signal-to-noise ratios was also designed by selecting wavelet parameters properly, which is expected to achieve higher accuracy and faster processing speed. For phase unwrapping, Poisson's equation with Neumann boundary condition was solved by using FFT. The benefit of using 2D-CWTs with different wavelets as compared to WFT was demonstrated experimentally.

关键词： Optical Metrology Windowed Fourier Transform (WFT) Two-dimensional Continuous wavelet Transform (2D-CWT) Phase Retrieval Phase Unwrapping Fringe Pattern Analysis

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Pansharpening via weighted additive wavelet transform

Pansharpening via weighted additive wavelet transform

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IEEE signal processing and Communications applications (SIU)

作者： Nur Hüseyin Kaplan Işın Erer Erzurum Teknik Universitesi Erzurum TR Istanbul Teknik Universitesi Istanbul TR

In additive wavelet transform (AWT) based classical pansharpening methods, the details of the panchromatic (PAN) image added to the multispectral (MS) image directly or by weighting after the detail extraction. In this paper, the details will be weighted during the detail extraction process. The details of the PAN image will be obtained by a weighted additive wavelet transform (WAWT). In order to achieve this aim, the range parameter of WAWT will be optimized for every image. The results obtained by the proposed method are compared with the classical AWT method, the context based method (CBD), and the enhanced CBD (ECB) method. It is observed that the proposed injection approach has better performance than the conventional weighted detail injection schemes.

关键词： Remote sensing Satellites wavelet transforms Geology Additives Filtering

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A new method for extraction of image's features: Complex discrete Ripplet-II transform

A new method for extraction of image's features: Complex dis...

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IEEE signal processing and Communications applications (SIU)

作者： Hüseyin Yaşar Murat Ceylan T.C Sağlık Bakanlığı Ankara Türkiye KTO Karatay Üniversitesi Mühendislik Fakültesi Elektrik-Elektronik Mühendisliği Bölümü Konya Türkiye

wavelet transform extracts the features of a signal and image via shifting and weighting methods. This transform has either advantages or disadvantages on image processing applications. One of important disadvantage of wavelet transform is limited orientation problem. This problem has been solved by different orientation with ridgelet transform. Ripplet-II transform is defined by recently generalising of the ridgelet transform by adding parameter degree (d). Complex discrete form of ripplet-II transform defined by this study and added to the literature. Also, complex discrete Ripplet-II transform was tested on medical image classification application. For this, the most common benign lesions in liver MR are classified as cyst and hemangioma using complex discrete Ripplet-II transform and ANN. Obtained results shown that, classification success of complex discrete Ripplet-II transform with complex-valued coefficients is higher than real-valued coefficients.

关键词： Radon Feature extraction wavelet transforms Liver Artificial neural networks

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Quality enhancement of compressed image based on perceptual modeling

Quality enhancement of compressed image based on perceptual ...

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conference on Advances in signal processing (CASP)

作者： Tushar R. Jadhav Samidha S. Thokare Riddhi B. Zaveri Department of Electronics and Telecommunication Vishwakarma Institute of Information Technology Pune India

ISBN: (纸本)9781509008506

wavelet algorithms have been generally learned for image processing purposes. image compression is the most common among these applications. But one of the main drawbacks of wavelet based compression is to disable quantization error efficiently. In this paper we have implemented a logarithmic model that estimates the non-linearity of human perception and somewhat precompensates for the effect of the display device. The model is based on Weber-Fechners law, which explains the differential sensitivity of the human perception using a logarithmic transfer function. To spread the coefficient distribution in the wavelet domain in compliance with the human perceptual attributes, a logarithmic transfer function is recommended by G. Al-Hudhud in his paper. Quantisation matrix is produced by calculating the values of standard deviation for all sub-bands for a given image. In order to provide the best visual quality of the processed image, the quantisation matrix is scaled. In JPEG the quantisation matrix is fixed for particular qualities for different images. But in this model, the main advantage is that, it produces quantisation matrix which is image dependent and scalable. Here we use this derived quantisation matrix to enhance the quality of the image and this matrix gives error less than the visibility threshold of human eye. The model presented in this paper is tested with grey scale images for various quality. The quality of reconstructed image is much better than the distorted image in terms of PSNR and MESSIM.

关键词： Quantization (signal) wavelet coefficients image coding Laplace equations Computational modeling Visualization

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Medical image illumination enhancement and sharpening by using stationary wavelet transform

Medical image illumination enhancement and sharpening by usi...

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IEEE signal processing and Communications applications (SIU)

作者： Pejman Rasti Morteza Daneshmand Fatih Alisinanoglu Cagri Ozcinar Gholamreza Anbarjafari ICV Research Group University of Tartu Tartu Estonia Dept. of Electrical and Electronic Eng. Hasan Kalyoncu University Gaziantep Turkey Institut Mines-Télécom Télécom ParisTech Paris France

Medical images captured by various devices have different illumination states based on chemicals used by patient prior to scanning. Consider a MRI image which has low contrast or is too bright, hence the experts cannot analysis that image due to poor representation of data in the image. In this paper we are proposing new medical image illumination enhancement and sharpening technique based on stationary wavelet transform which is addressing the aforementioned problem. The technique decomposes the input medical image into the four frequency subbands by using stationary wavelet transformation and enhances the illumination of the low-low subband image, and then it enhanced edges of image by adding the high frequency subbands to the image. The technique is compared with the conventional and state-of-art image illumination enhancement techniques such as histogram equalisation, local histogram equalisation, singular value equalisation, and discrete wavelet transform followed by singular value decomposition contrast enhancement techniques. The experimental results are showing the superiority of the proposed method over the conventional and the state-of-art techniques.

关键词： Lighting Discrete wavelet transforms Biomedical imaging Histograms Brightness image edge detection

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RDWT and SVD based secure digital image watermarking using ACM

RDWT and SVD based secure digital image watermarking using A...

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IEEE signal processing and Communications applications (SIU)

作者： LLukman Çerkezi Gökçen Çetinel Sakarya Universitesi Sakarya TR

In this study, digital image watermarking method based on Redundant Discrete wavelet Transform (RDWT) and Singular value Decomposition (SVD) is proposed. By exploiting the complexity property of the chaotic signals, which is the main reason of using them in the security applications, the robustness and the invisibility of the proposed method is improved. In the proposed watermarking scheme, RDWT is performed to decompose the cover image into four sub-bands (LL, LH, HL and HH). Then SVD is applied to the LL sub-band of the cover image. The chaotic watermark is generated by applying Arnold Cat Map (ACM) to the original watermark. Finally, singular values of the LL sub-band of the cover image are modified with the singular values of the chaotic watermark according to the embedding process. It is demonstrated via computer simulations that the proposed RDWT, SVD and ACM based digital image watermarking scheme provides better watermark concealment and high robustness against both geometric and image processing attacks. Furthermore, the robustness of the proposed scheme is investigated for different dimensions of the binary watermark logo. It is shown that the robustness of our method is independent of the watermark size.

关键词： Watermarking Discrete wavelet transforms Robustness Digital images Singular value decomposition

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