International Journal of Signal and Imaging Systems Engineering http://www.inderscience.com/browse/index.php?journalID=185&year=2011&vol=4&issue=4 Inderscience Publishers Ltd en-uk International Journal of Signal and Imaging Systems Engineering 1748-0698 1748-0701 © 2011 Inderscience Publishers Ltd editor@inderscience.com https://www.inderscience.com/images/files/coverImgs/ijsise_scoverijsise.jpg http://www.inderscience.com/browse/index.php?journalID=185&year=2011&vol=4&issue=4 http://www.inderscience.com/link.php?id=44606 A novel Adaptive Lossy Compression technique, namely Least Probable Coefficients Approximation (LPCA) technique, is proposed to achieve better performance and simpler implementation than JPEG at low bitrate. Compression using LPCA based on reducing the number of source symbols by applying efficient processing on the Discrete Cosine Transform (DCT) coefficients of the image in addition to efficient quantisation to reduce the transmitted values. It is a general compression technique that can be applied to any digital data not just images. Experimental comparisons are carried out to compare the performance of the proposed technique with that of JPEG. The experimental results show that: The proposed compression technique achieves high Compression Ratio (CR) with higher Signal to Noise Ratio (SNR) than that of JPEG at low bitrate without the great visual degradation that appears in case of JPEG. Image compression using Least Probable Coefficients Approximation technique
Shaimaa A. El-said; Khalid F.A. Hussein; Mohamed M. Fouad
International Journal of Signal and Imaging Systems Engineering, Vol. 4, No. 4 (2011) pp. 197 - 206
A novel Adaptive Lossy Compression technique, namely Least Probable Coefficients Approximation (LPCA) technique, is proposed to achieve better performance and simpler implementation than JPEG at low bitrate. Compression using LPCA based on reducing the number of source symbols by applying efficient processing on the Discrete Cosine Transform (DCT) coefficients of the image in addition to efficient quantisation to reduce the transmitted values. It is a general compression technique that can be applied to any digital data not just images. Experimental comparisons are carried out to compare the performance of the proposed technique with that of JPEG. The experimental results show that: The proposed compression technique achieves high Compression Ratio (CR) with higher Signal to Noise Ratio (SNR) than that of JPEG at low bitrate without the great visual degradation that appears in case of JPEG.

]]> 10.1504/IJSISE.2011.044606 International Journal of Signal and Imaging Systems Engineering, Vol. 4, No. 4 (2011) pp. 197 - 206 Shaimaa A. El-said; Khalid F.A. Hussein; Mohamed M. Fouad Faculty of Engineering, Electronics and Communications Department, Zagazig University, P.O. 44519, Zagazig, Egypt. ' Electronics Research Institute/Microwaves Department, Researches National Institute, Dokki, P.O. 16354, Egypt. ' Faculty of Engineering, Electronics and Communications Department, Zagazig University, P.O. 44519, Zagazig, Egypt image compression adaptive quantisation DCT discrete cosine transform general compression technique Huffman encoding JPEG adaptive lossy compression image processing. 2011-12-31T23:20:50-05:00 4 4 197 206 2011-12-31T23:20:50-05:00 http://www.inderscience.com/link.php?id=44534 In this paper, a new improved low complexity compression methodology named as Near Lossless Image Compression (NLIC) has been suggested. This algorithm is a hybrid method which includes DCT, a lossy compression technique and JPEG encoding using entropy based Huffman coding, a lossless compression technique. The algorithm is tested with standard square images of sizes 512 × 512 and 1024 × 1024 respectively. The results of NLIC are also compared with the Huffman and Run length Encoding (RLE) for evaluating its compression efficiency. An improved low complexity Near Lossless Image Compression
Mohit Kumar Gupta; Narendra D. Londhe
International Journal of Signal and Imaging Systems Engineering, Vol. 4, No. 4 (2011) pp. 207 - 211
In this paper, a new improved low complexity compression methodology named as Near Lossless Image Compression (NLIC) has been suggested. This algorithm is a hybrid method which includes DCT, a lossy compression technique and JPEG encoding using entropy based Huffman coding, a lossless compression technique. The algorithm is tested with standard square images of sizes 512 × 512 and 1024 × 1024 respectively. The results of NLIC are also compared with the Huffman and Run length Encoding (RLE) for evaluating its compression efficiency.

]]> 10.1504/IJSISE.2011.044534 International Journal of Signal and Imaging Systems Engineering, Vol. 4, No. 4 (2011) pp. 207 - 211 Mohit Kumar Gupta; Narendra D. Londhe Department of Electrical Engineering, National Institute of Technology (NIT) Raipur, Raipur 492010 (C.G.), India. ' Department of Electrical Engineering, National Institute of Technology (NIT) Raipur, Raipur 492010 (C.G.), India low complexity image compression DCT discrete cosine transform Huffman NLIC near lossless image compression RLE run length encoding. 2011-12-31T23:20:50-05:00 4 4 207 211 2011-12-31T23:20:50-05:00 http://www.inderscience.com/link.php?id=44533 Distributed Video Coding (DVC) is a new video coding paradigm, the main objective of which is to reduce the encoder complexity to support a separate class of uplink-friendly applications like wireless video applications, besides achieving the rate-distortion performance of conventional video coders. In this paper, we describe and present the simulation results of the video coding method based on the principle of distributed source coding using Golay codes and then propose an improvement to it. In this, the side information is improved by performing a very coarse motion search at the encoder and transmitting the position of the side information block as the hash information to the decoder, which will help the decoder to perform motion estimation. Efficient Distributed Video Coding based on principle of syndrome coding
P. Aparna; Sumam David
International Journal of Signal and Imaging Systems Engineering, Vol. 4, No. 4 (2011) pp. 212 - 219
Distributed Video Coding (DVC) is a new video coding paradigm, the main objective of which is to reduce the encoder complexity to support a separate class of uplink-friendly applications like wireless video applications, besides achieving the rate-distortion performance of conventional video coders. In this paper, we describe and present the simulation results of the video coding method based on the principle of distributed source coding using Golay codes and then propose an improvement to it. In this, the side information is improved by performing a very coarse motion search at the encoder and transmitting the position of the side information block as the hash information to the decoder, which will help the decoder to perform motion estimation.

]]> 10.1504/IJSISE.2011.044533 International Journal of Signal and Imaging Systems Engineering, Vol. 4, No. 4 (2011) pp. 212 - 219 P. Aparna; Sumam David Department of Electronics and Communication Engineering, National Institute of Technology Karnataka Surathkal, Mangalore, India. ' Department of Electronics and Communication Engineering, National Institute of Technology Karnataka Surathkal, Mangalore, India syndrome coding coset wireless video DVC distributed video coding simulation motion estimation. 2011-12-31T23:20:50-05:00 4 4 212 219 2011-12-31T23:20:50-05:00 http://www.inderscience.com/link.php?id=44537 This paper proposed an adaptive denoising approach, which fuses the images denoised by Total Variation (TV), curvelet-based method and edge information. Edge information is extracted from the noise residue of TV method by processing it through curvelet transform. The denoising abilities of the proposed method are evaluated on standard Lena image as well as on brain Computed Tomography (CT) images. Experimental results show that the proposed approach reduces the staircase effect caused by TV method and also reduces fuzzy edges induced by curvelet transform in the homogeneous areas of the image. This proposed adaptive fusion-based approach gives superior results not only for noise suppression but also for edge preservation. Image denoising based on adaptive fusion of curvelet transform and Total Variation
H.S. Bhadauria; M.L. Dewal
International Journal of Signal and Imaging Systems Engineering, Vol. 4, No. 4 (2011) pp. 220 - 227
This paper proposed an adaptive denoising approach, which fuses the images denoised by Total Variation (TV), curvelet-based method and edge information. Edge information is extracted from the noise residue of TV method by processing it through curvelet transform. The denoising abilities of the proposed method are evaluated on standard Lena image as well as on brain Computed Tomography (CT) images. Experimental results show that the proposed approach reduces the staircase effect caused by TV method and also reduces fuzzy edges induced by curvelet transform in the homogeneous areas of the image. This proposed adaptive fusion-based approach gives superior results not only for noise suppression but also for edge preservation.

]]> 10.1504/IJSISE.2011.044537 International Journal of Signal and Imaging Systems Engineering, Vol. 4, No. 4 (2011) pp. 220 - 227 H.S. Bhadauria; M.L. Dewal Department of Electrical Engineering, Indian Institute of Technology, Roorkee 247667, India. ' Department of Electrical Engineering, Indian Institute of Technology, Roorkee 247667, India curvelet transform total variation computed tomography image denoising adaptive fusion image processing staircase effect fuzzy edges noise suppression edge preservation. 2011-12-31T23:20:50-05:00 4 4 220 227 2011-12-31T23:20:50-05:00 http://www.inderscience.com/link.php?id=44540 The Paper, the proposed research experimentation has been established in Central Foundry Forge Plant (CFFP) of Bharat Heavy Electrical Ltd. India (BHEL). The proposed image segmentation techniques are introduced to detect and assess the weld flaws from the weldments and calculate the features such as length, width, area, perimeter, major axis length, minor axis length, orientation and resolution. Software has fully written in Matlab. A comparative table showing the results is also presented in the paper. The proposed algorithm is faster and achieves favourable results. The results are validated with standard Non-Destructive Testing (NDT) methods. Analysis of radiographical weld flaws using image-processing approach
Vijay R. Rathod; R.S. Anand; Alaknanda Ashok
International Journal of Signal and Imaging Systems Engineering, Vol. 4, No. 4 (2011) pp. 228 - 237
The Paper, the proposed research experimentation has been established in Central Foundry Forge Plant (CFFP) of Bharat Heavy Electrical Ltd. India (BHEL). The proposed image segmentation techniques are introduced to detect and assess the weld flaws from the weldments and calculate the features such as length, width, area, perimeter, major axis length, minor axis length, orientation and resolution. Software has fully written in Matlab. A comparative table showing the results is also presented in the paper. The proposed algorithm is faster and achieves favourable results. The results are validated with standard Non-Destructive Testing (NDT) methods.

]]> 10.1504/IJSISE.2011.044540 International Journal of Signal and Imaging Systems Engineering, Vol. 4, No. 4 (2011) pp. 228 - 237 Vijay R. Rathod; R.S. Anand; Alaknanda Ashok Department of Electrical Engineering, Indian Institute of Technology, Roorkee, Roorkee 247667, India. ' Department of Electrical Engineering, Indian Institute of Technology, Roorkee, Roorkee 247667, India. ' Department of Electrical Engineering, Indian Institute of Technology, Roorkee, Roorkee 247667, India radiographic images weld flaws NDT nondestructive testing edge-based segmentation watershed segmentation markers watershed segmentation dimension analysis image processing welding. 2011-12-31T23:20:50-05:00 4 4 228 237 2011-12-31T23:20:50-05:00 http://www.inderscience.com/link.php?id=44541 Curvature driven diffusion is widely used for image denoising and inpainting. Among the curvature driven diffusion techniques Gauss Curvature Driven Diffusion (GCDD) became a prominent image denoising method due to its capability to retain some important structures with non zero curvatures, like curved edges, corners etc. Unlike many other non-linear diffusion techniques, the curvature driven diffusion hardly has any inverse diffusion characteristics. In this work we propose to introduce a shock term along with the GCDD term to enhance the edges while smoothing-out the noise. This technique will preserve some important structures and enhance them while denoising the image. The experiments clearly demonstrates the efficiency of the method. Curvature driven diffusion coupled with shock for image enhancement/reconstruction
P. Jidesh; Santhosh George
International Journal of Signal and Imaging Systems Engineering, Vol. 4, No. 4 (2011) pp. 238 - 247
Curvature driven diffusion is widely used for image denoising and inpainting. Among the curvature driven diffusion techniques Gauss Curvature Driven Diffusion (GCDD) became a prominent image denoising method due to its capability to retain some important structures with non zero curvatures, like curved edges, corners etc. Unlike many other non-linear diffusion techniques, the curvature driven diffusion hardly has any inverse diffusion characteristics. In this work we propose to introduce a shock term along with the GCDD term to enhance the edges while smoothing-out the noise. This technique will preserve some important structures and enhance them while denoising the image. The experiments clearly demonstrates the efficiency of the method.

]]> 10.1504/IJSISE.2011.044541 International Journal of Signal and Imaging Systems Engineering, Vol. 4, No. 4 (2011) pp. 238 - 247 P. Jidesh; Santhosh George Department of Mathematical and Computational Sciences, National Institute of Technology Karnataka, Mangalore 575 025, India. ' Department of Mathematical and Computational Sciences, National Institute of Technology Karnataka, Mangalore 575 025, India diffusion image enhancement shock filters Gauss curvature image reconstruction image denoising image processing. 2011-12-31T23:20:50-05:00 4 4 238 247 2011-12-31T23:20:50-05:00 http://www.inderscience.com/link.php?id=44550 The paper presents results of compression using Run Length Encoding (RLE) scheme on speech signals of International Phonetic Alphabet (IPA) database. These speech signals are compressed with no noise being added then they are compressed after adding some noise to them. It observed that RLE scheme gives high Compression Ratio (CR) for noisy speech signal compared to non noisy speech signal. The performance of RLE scheme on standard speech signal as well as noisy speech signal is compared with compression by Huffman coding. The obtained results indicate that RLE scheme gives high CR compared to CR by Huffman coding. Effect of noise on speech compression in Run Length Encoding scheme
Mohammad Arif; R.S. Anand
International Journal of Signal and Imaging Systems Engineering, Vol. 4, No. 4 (2011) pp. 248 - 256
The paper presents results of compression using Run Length Encoding (RLE) scheme on speech signals of International Phonetic Alphabet (IPA) database. These speech signals are compressed with no noise being added then they are compressed after adding some noise to them. It observed that RLE scheme gives high Compression Ratio (CR) for noisy speech signal compared to non noisy speech signal. The performance of RLE scheme on standard speech signal as well as noisy speech signal is compared with compression by Huffman coding. The obtained results indicate that RLE scheme gives high CR compared to CR by Huffman coding.

]]> 10.1504/IJSISE.2011.044550 International Journal of Signal and Imaging Systems Engineering, Vol. 4, No. 4 (2011) pp. 248 - 256 Mohammad Arif; R.S. Anand Department of Electrical Engineering, Indian Institute of Technology Roorkee, Roorkee 247667, Uttarakhand, India. ' Department of Electrical Engineering, Indian Institute of Technology Roorkee, Roorkee 247667, Uttarakhand, India speech compression IPA International Phonetics Alphabet noise corrupted signals compression ratio hearing quality RLE run length encoding compressed speech signals Huffman coding. 2011-12-31T23:20:50-05:00 4 4 248 256 2011-12-31T23:20:50-05:00