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Title |
Fast Indexing of Lattice Vectors for Image Compression |
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Author |
R. R. Khandelwal, P. K. Purohit, S. K. Shriwastava |
| Citation |
Vol. 12 No. 5 pp. 85-89 |
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Abstract |
Visual communication is becoming increasingly important with applications in several areas such as multimedia, communication, data transmission and storage of remote sensing images, satellite images, education, medical etc….The image data occupies large space. Meeting bandwidth requirements and maintaining acceptable image quality simultaneously is a challenge. Hence image compression is required. There are mainly two types of compression systems- lossy and lossless. When quantization is involved in compression process, compression will be a lossy compression. Lattice Vector Quantization is a simple but powerful tool for vector quantization. After quantization of vectors using lattice structure, indexing of lattice vectors is required. In this work our attention is on the problem of efficient indexing. MSE and PSNR of different images using proposed method are calculated. Perceptual performance of image coding is also shown in the result. |
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Keywords |
Lattice Vector Quantization(LVQ), Mean Square Error(MSE), Peak Signal to Noise Ratio(PSNR) |
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