The Experts below are selected from a list of 1128 Experts worldwide ranked by ideXlab platform
Narendra Singh - One of the best experts on this subject based on the ideXlab platform.
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Image Compression Based On Multiple Parameter Discrete Fractional Fourier Transform for Satellite and Medical Images
2015Co-Authors: Deepak Sharma, Rajiv Saxena, Narendra SinghAbstract:With the growing demand of high quality multimedia (HD) the data size has increased thus the compression is the essential requirement to process and store data with smaller size. The Multiple Parameter Discrete Fractional Fourier Transform (MPDFRFT) is generalization of the discrete fractional Fourier Transform and can be use for compression of high resolution Images with the extra degree of freedom provided by the MPDFRFT and its different fractional orders finally Decompressed Image can also be recovered. This paper deals with the Image compression based on MPDFRFT using Eigen vector decomposition algorithm. The MPDFRFT possesses all the desired properties of discrete fractional Fourier transform. The MPDFRFT converts to the DFRFT when all of its order parameters are the same. We exploit the properties of multiple-parameter DFRFT and propose a novel compression scheme for satellite and medical Images more conveniently than urban, rural and natural Images. In this scheme Image is subdivided and MPDFRFT is applied for the subdivided Image to form transformed coefficients and Inverse MPDFRFT is applied for reconstruction of original Images. The proposed compression scheme with MPDFRFT significantly show
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hybrid encryption compression scheme based on multiple parameter discrete fractional fourier transform with eigen vector decomposition algorithm
International Journal of Computer Network and Information Security, 2014Co-Authors: Deepak Sharma, Rajiv Saxena, Narendra SinghAbstract:Encryption along with compression is the process used to secure any multimedia content processing with minimum data storage and transmission. The transforms plays vital role for optimizing any encryptioncompression systems. Earlier the original information in the existing security system based on the fractional Fourier transform (FRFT) is protected by only a certain order of FRFT. In this article, a novel method for encryption-compression scheme based on multiple parameters of discrete fractional Fourier transform (DFRFT) with random phase matrices is proposed. The multiple-parameter discrete fractional Fourier transform (MPDFRFT) possesses all the desired properties of discrete fractional Fourier transform. The MPDFRFT converts to the DFRFT when all of its order parameters are the same. We exploit the properties of multipleparameter DFRFT and propose a novel encryptioncompression scheme using the double random phase in the MPDFRFT domain for encryption and compression data. The proposed scheme with MPDFRFT significantly enhances the data security along with Image quality of Decompressed Image compared to DFRFT and FRFT and it shows consistent performance with different Images. The numerical simulations demonstrate the validity and efficiency of this scheme based on Peak signal to noise ratio (PSNR), Compression ratio (CR) and the robustness of the schemes against bruit force attack is examined.
Patrick Le Callet - One of the best experts on this subject based on the ideXlab platform.
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Tone mapping-based high-dynamic-range Image compression: study of optimization criterion and perceptual quality
Optical Engineering, 2013Co-Authors: Manish Narwaria, Matthieu Perreira Da Silva, Patrick Le Callet, Romuald PépionAbstract:We study the issue of quality assessment in tone mapping- based high-dynamic-range (HDR) Image compression. In this, there are two stages at which a decision should be made regarding perceptual vis- ual quality: (a) for finding the optimal parameters of the dynamic range reduction function so that the visual quality is maximized, and (b) visual quality judgment of the Decompressed Image. We first investigate two objective optimization criteria, namely mean squared error and structural similarity index measure, toward optimization of a tone mapping model- based HDR Image compression method. We then conduct a comprehen- sive subjective study to evaluate the visual quality of the compressed HDR Images. Therefore, we consider both objective and subjective aspects for HDR Image compression. To our knowledge, no systematic and compre- hensive studies exist in the current literature which shed light on the issue of quality assessment in HDR compression. So this study brings in new knowledge and perspective for the relatively less investigated topic of HDR compression from the view point of perceptual quality. We further evaluate the prediction performances of four objective methods on the 140 compressed HDR Images that have been subjectively rated.
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Objective quality assessment of color Images based on a generic perceptual reduced reference
Signal Processing: Image Communication, 2008Co-Authors: Mathieu Carnec, Patrick Le Callet, Dominique BarbaAbstract:When an Image is supposed to have been transformed by a process like Image enhancement or lossy Image compression for storing or transmission, it is often necessary to measure the quality of the distorted Image. This can be achieved using an Image processing method called “quality criterion”. Such a process must produce objective quality scores in close relationship with subjective quality scores given by human observers during subjective quality assessment tests. In this paper, an Image quality criterion is proposed. This criterion, called C4, is fully generic (i.e., not designed for predefined distortion types or for particular Images types) and based on a rather elaborate model of the human visual sys- tem (HVS). This model describes the organization and operation of many stages of vision, from the eye to the ventral and dorsal pathways in the visual cortex. The novelty of this quality criterion relies on the extraction, from an Image rep- resented in a perceptual space, of visual features that can be compared to those used by the HVS. Then a similarity metric computes the objective quality score of a distorted Image by comparing the features extracted from this Image to features extracted from its reference Image (i.e., not distorted). Results show a high correla- tion between produced objective quality scores and subjective ones, even for Images that have been distorted through several different distortion processes. To illus- trate these performances, they have been computed using three different databases that employed different contents, distortions type, displays, viewing conditions and subjective protocols. The features extracted from the reference Image constitute a reduced reference which, in a transmission context with data compression, can be computed at the sender side and transmitted in addition to the compressed Image data so that the quality of the Decompressed Image can be objectively assessed at the receiver side. More, the size of the reduced reference is flexible. This work has been integrated into freely available applications in order to formulate a practical alternative to the PSNR criterion which is still too often used despite its low cor- relation with human judgments. These applications also enable quality assessment for Image transmission purposes.
Deepak Sharma - One of the best experts on this subject based on the ideXlab platform.
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Image Compression Based On Multiple Parameter Discrete Fractional Fourier Transform for Satellite and Medical Images
2015Co-Authors: Deepak Sharma, Rajiv Saxena, Narendra SinghAbstract:With the growing demand of high quality multimedia (HD) the data size has increased thus the compression is the essential requirement to process and store data with smaller size. The Multiple Parameter Discrete Fractional Fourier Transform (MPDFRFT) is generalization of the discrete fractional Fourier Transform and can be use for compression of high resolution Images with the extra degree of freedom provided by the MPDFRFT and its different fractional orders finally Decompressed Image can also be recovered. This paper deals with the Image compression based on MPDFRFT using Eigen vector decomposition algorithm. The MPDFRFT possesses all the desired properties of discrete fractional Fourier transform. The MPDFRFT converts to the DFRFT when all of its order parameters are the same. We exploit the properties of multiple-parameter DFRFT and propose a novel compression scheme for satellite and medical Images more conveniently than urban, rural and natural Images. In this scheme Image is subdivided and MPDFRFT is applied for the subdivided Image to form transformed coefficients and Inverse MPDFRFT is applied for reconstruction of original Images. The proposed compression scheme with MPDFRFT significantly show
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hybrid encryption compression scheme based on multiple parameter discrete fractional fourier transform with eigen vector decomposition algorithm
International Journal of Computer Network and Information Security, 2014Co-Authors: Deepak Sharma, Rajiv Saxena, Narendra SinghAbstract:Encryption along with compression is the process used to secure any multimedia content processing with minimum data storage and transmission. The transforms plays vital role for optimizing any encryptioncompression systems. Earlier the original information in the existing security system based on the fractional Fourier transform (FRFT) is protected by only a certain order of FRFT. In this article, a novel method for encryption-compression scheme based on multiple parameters of discrete fractional Fourier transform (DFRFT) with random phase matrices is proposed. The multiple-parameter discrete fractional Fourier transform (MPDFRFT) possesses all the desired properties of discrete fractional Fourier transform. The MPDFRFT converts to the DFRFT when all of its order parameters are the same. We exploit the properties of multipleparameter DFRFT and propose a novel encryptioncompression scheme using the double random phase in the MPDFRFT domain for encryption and compression data. The proposed scheme with MPDFRFT significantly enhances the data security along with Image quality of Decompressed Image compared to DFRFT and FRFT and it shows consistent performance with different Images. The numerical simulations demonstrate the validity and efficiency of this scheme based on Peak signal to noise ratio (PSNR), Compression ratio (CR) and the robustness of the schemes against bruit force attack is examined.
Jauji Shen - One of the best experts on this subject based on the ideXlab platform.
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a discrete wavelet transform based state codebook search algorithm for vector quantization
International Conference on Innovative Computing Information and Control, 2006Co-Authors: Chinchen Chang, Yungchen Chou, Jauji ShenAbstract:Side match vector quantization method collects the possible codewords by using partial pixels of neighboring blocks. Furthermore, the state codebook design provides a way to improve compression ratio. In the complex content Image, side match vector quantization method has a lower compression performance. The proposed method utilizes the property of discrete wavelet transform to save the computation cost for finding a suitable codeword. Moreover, a well designed novel state codebook by observing the characteristics of Images in order to improve the compression ratio. In the test of smooth Images, the visual quality of Decompressed Image by using our proposed method has approximated to the full search vector quantization. Moreover, the compression ratio for complex content Images has a better performance than full search vector quantization and side match vector quantization.
Wenjun Zeng - One of the best experts on this subject based on the ideXlab platform.
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Scalable Lossy Compression for Pixel-Value Encrypted Images
2012 Data Compression Conference, 2012Co-Authors: Xiangui Kang, Xianyu Xu, Anjie Peng, Wenjun ZengAbstract:Compression of encrypted data draws much attention in recent years due to the security concerns in a service oriented environment such as cloud computing. We propose a scalable lossy compression scheme for Images having their pixel value encrypted with a standard stream cipher. The encrypted data are simply compressed by transmitting a uniformly sub sampled portion of the encrypted data and some bit-planes of another uniformly sub sampled portion of the encrypted data. With a proposed content adaptive interpolation prediction method with side information, at the receiver side, a decoder performs content adaptive interpolation based on the decrypted partial information, where the received bit-plane information serves as the side information that reflects the Image edge information, making the Image reconstruction more precise. When more bit-planes are transmitted, higher quality of the Decompressed Image can be achieved. The experimental results show that our proposed scheme achieves much better performance than the existing lossy compression scheme for pixel value encrypted Images, and also similar performance as the state-of-the-art lossy compression for pixel permutation based encrypted Images. In addition, our proposed scheme has the following advantages: at the decoder side, no computationally intensive iteration and no additional public orthogonal matrix is needed. It works well for both smooth and texture-rich Images.
