| Journal: | Journal of applied research and technology |
| Database: | PERIÓDICA |
| System number: | 000367699 |
| ISSN: | 1665-6423 |
| Authors: | Raza, Mudassar1 Adnan, Ahmed1 Sharif, Muhammad1 Haider, Syed Waqas1 |
| Institutions: | 1COMSATS Institute of Information Technology, Department of Computer Sciences, Wah Cantt. Pakistán |
| Year: | 2012 |
| Season: | Ago |
| Volumen: | 10 |
| Number: | 4 |
| Pages: | 618-628 |
| Country: | México |
| Language: | Inglés |
| Document type: | Artículo |
| Approach: | Experimental, aplicado |
| English abstract | Space research organizations, hospitals and military air surveillance activities, among others, produce a huge amount of data in the form of images hence a large storage space is required to record this information. In hospitals, data produced during medical examination is in the form of a sequence of images and are very much correlated; because these images have great importance, some kind of lossless image compression technique is needed. Moreover, these images are often required to be transmitted over the network. Since the availability of storage and bandwidth is limited, a compression technique is required to reduce the number of bits to store these images and take less time to transmit them over the network. For this purpose, there are many state-of the-art lossless image compression algorithms like CALIC, LOCO-I, JPEG-LS, JPEG20000; Nevertheless, these compression algorithms take only a single file to compress and cannot exploit the correlation among the sequence frames of MRI or CE images. To exploit the correlation, a new algorithm is proposed in this paper. The primary goals of the proposed compression method are to minimize the memory resource during storage of compressed data as well as minimize the bandwidth requirement during transmission of compressed data. For achieving these goals, the proposed compression method combines the single image compression technique called super spatial structure prediction with inter-frame coding to acquire grater compression ratio. An efficient compression method requires elimination of redundancy of data during compression; therefore, for elimination of redundancy of data, initially, the super spatial structure prediction algorithm is applied with the fast block matching approach and later Huffman coding is applied for reducing the number of bits required for transmitting and storing single pixel value. Also, to speed up the block-matching process during motion estimat |
| Disciplines: | Ciencias de la computación |
| Keyword: | Procesamiento de datos, Manejo de imágenes, Compresión de imágenes, Imágenes médicas, Secuencias de imágenes |
| Keyword: | Computer science, Data processing, Images management, Image compression, Medical images, Image sequences |
| Full text: | Texto completo (Ver HTML) |
