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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  

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... 

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... 

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... 

In this paper, an algorithm for image coding based on a sparse 3-dimensional Discrete Cosine Transform (3D DCT) is studied. The algorithm is essentially a method for achieving a sufficiently sparse representation using 3D DCT. The experimental results obtained by the algorithm are compared to the 2D DCT (used in JPEG standard) and wavelet db9/7 (used in JPEG2000 standard). It is experimentally shown that the algorithm, that only uses DCT but in 3 dimensions, outperforms the DCT used in JPEG standard and achieves comparable results (but still less than) the wavelet transform. © Springer-Verlag Berlin Heidelberg 2009  

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...