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lossless-compression
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Processing Images with Hexagonal Pixels
, M.Sc. Thesis Sharif University of Technology ; Mahdavi Amiri, Nezameddin (Supervisor)
Abstract
Image processing is very important in several applications. Here we use a rectangular grid for image processing. Other approaches exist in the literature. One new approach is to change the grid from rectangular to hexagonal, due to its various advantages over the latter. Main advantage of the hexagonal structure in image processing is its resemblance with the arrangement of photoreceptors in the human eyes. The change in arrangement amounts to requiring less pixels. There is no inconsistency in pixel connectivity and thus angular resolution is higher in this arrangement. Our goal here is to study lossless compression algorithms for images with hexagonal pixels. First, we consider the...
Efficient Hardware Implementation of Lossless Medical Image Compression
, M.Sc. Thesis Sharif University of Technology ; Mortazavi, Mohammad (Supervisor) ; Ghorshi, Mohammad Ali (Co-Advisor)
Abstract
Medical images contain human body pictures and are widely used for diag-nosis and surgical purposes. Compression is needed for medical images for some applications such as profiling a patient's data or transmission systems. Due to the importance of the information of medical images, lossless or visually lossless compression is preferred. Lossless compression mainly consists of transformation and encoding steps. On the other hand, hardware implementation of lossless compression algorithm accelerates real time tasks such as online diagnosis and telemedicine. Lossless JPEG, JPEG-LS and lossless version of JPEG2000 are few well known methods for lossless compression. In this thesis, we introduce...
Simple lossless and near-lossless medical image compression based on enhanced DPCM transformation
, Article IEEE Pacific RIM Conference on Communications, Computers, and Signal Processing - Proceedings ; 2011 , Pages 66-72 ; 9781457702518 (ISBN) ; Mortazavi, M ; Ghorshi, S ; Choupan, J ; Sharif University of Technology
2011
Abstract
Medical images include information about human body which are used for different purposes such as surgical and diagnostic plans. Compression of medical images is used in some applications such as profiling patient's data and transmission systems. Regard to importance of medical images information, lossless or near-lossless compression is preferred. Lossless JPEG, JPEG-LS and lossless version of JPEG2000 are few well-known methods for lossless compression. JPEG2000 is one of the latest and provides good compression ratio, however, it is complex [1]. In real time application which needs hardware implementation, low complex algorithm accelerates compression process. In this paper, a lossless...
Efficient medical image transformation method for lossless compression by considering real time applications
, Article 4th International Conference on Signal Processing and Communication Systems, ICSPCS'2010 - Proceedings, 13 December 2010 through 15 December 2010, Gold Coast, QLD ; 2010 ; 9781424479078 (ISBN) ; Mortazavi, M ; Ghorshi, S ; Choupan, J ; Sharif University of Technology
2010
Abstract
Medical images contain human body pictures and used widely in diagnosis and surgical purposes [1]. Compression is needed for medical images for some applications such as profiling patient's data or transmission systems Due to the importance of the information of medical images, lossless or visually lossless compression preferred. Lossless compression mainly consists of transformation and encoding steps. On the other hand, hardware implementation of lossless compression algorithm accelerates real time tasks such as online diagnosis and telemedicine. Lossless JPEG, JPEG-LS and lossless version of JPEG2000 are few well known methods for lossless compression. This paper is focused on the...
Binary hybrid GA-PSO based algorithm for compression of hyperspectral data
, Article 5th International Conference on Signal Processing and Telecommunication Systems, ICSPCS'2011, Honolulu, HI, 12 December 2011 through 14 December 2011 ; 2011 ; 9781457711800 (ISBN) ; Sepehrband, F ; Choupan, J ; Mortazavi, M ; Sharif University of Technology
Abstract
This paper introduces two new compression methods. One of these methods is adaptive and powerful for the compression of hyperspectral data, which is based on separating the bands with different specifications by the histogram analyzes and new version of Binary Hybrid GA-PSO (BHGAPSO) and compressing each one with a different manner. The new proposed methods improve the compression ratio of the JPEG standards and save storage space the transmission system. The proposed methods are applied on different test cases, and the results are evaluated and compared with some other compression methods, such as lossless JPEG and JPEG2000
New rectangular partitioning methods for lossless binary image compression
, Article International Conference on Signal Processing Proceedings, ICSP, 24 October 2010 through 28 October 2010 ; 2010 , Pages 694-697 ; 9781424458981 (ISBN) ; Hosseini, H ; Beygiharchegani, S ; Pad, P ; Marvasti, F ; Sharif University of Technology
Abstract
In this paper, we propose two lossless compression techniques that represent a two dimensional Run-length Coding which can achieve high compression ratio. This method works by partitioning the block regions of the input image into rectangles instead of working by runs of adjacent pixels, so it is found to be more efficient than 1D RLE Run-length Coding for transmitting texts and image. In the first method, length and width of consecutive black and white rectangles are transmitted. The idea of this method is new and it can be very effective for some images which have large blocks of black or white pixels. But in the second method only black rectangles are considered in order to transmit and...
An efficient lossless medical image transformation method by improving prediction model
, Article International Conference on Signal Processing Proceedings, ICSP, 24 October 2010 through 28 October 2010 ; 2010 , Pages 728-731 ; 9781424458981 (ISBN) ; Mortazavi, M ; Ghorshi, S ; IEEE Beijing Section; The Chinese Institute of Electronics (CIE); The Institution of Engineering and Technology (IET); Union Radio Scientifique Internationale (URSI); National Natural Science Foundation of China ; Sharif University of Technology
Abstract
Medical images include human body picture and it is used in diagnosis purpose [1]. Lossless compression of medical image is an application of medical imaging. During lossless compression task, transformation algorithm can be used to increase compression ratio. In Real time applications such as telemedicine and online diagnosis, hardware implementation accelerates the process. Hence, for such purposes medical compression is better to be simple. Lossless JPEG and JPEG2000 are some compression method. JPEG2000 gives better compression ratio. However, it is complex. In this paper an efficient method of lossless image transformation has been introduced by improving prediction model. Simulation...
Roi-based 3D human brain magnetic resonance images compression using adaptive mesh design and region-based discrete wavelet transform
, Article International Journal of Wavelets, Multiresolution and Information Processing ; Volume 8, Issue 3 , 2010 , Pages 407-430 ; 02196913 (ISSN) ; Shooshtari, P ; Sharif University of Technology
Abstract
Due to the large volume required for medical images for transmission and archiving purposes, the compression of medical images is known as one of the main concepts of medical image processing. Lossless compression methods have the drawback of a low compression ratio. In contrast, lossy methods have a higher compression ratio and suffer from lower quality of the reconstructed images in the receiver. Recently, some selective compression methods have been proposed in which the main image is divided into two separate regions: Region of Interest (ROI), which should be compressed in a lossless manner, and Region of Background (ROB), which is compressed in a lossy manner with a lower quality. In...
Simple and efficient remote sensing image transformation for lossless compression
, Article Proceedings of SPIE - The International Society for Optical Engineering ; Volume 8285 , 2011 ; 0277786X (ISSN) ; 9780819489326 (ISBN) ; Ghamisi, P ; Mortazavi, M ; Choupan, J ; Sharif University of Technology
2011
Abstract
Remote Sensing (RS) images or satellite images include information about earth. Compression of RS images is important in the field of satellite transmission systems and mass storage purposes. Because of importance of information and existent of large amount of details, lossless compression preferred. Real time compression technique is applied on satellite and aerial transmission systems [1]. A simple algorithm accelerates the whole process in real time purposes. Lossless JPEG, JPEG-LS and JPEG2000 are some famous lossless compression methods. Transformation is the first step of these methods. In this paper, a simple and efficient method of lossless image transformation has been introduced by...