22-08-2013, 01:01 PM
Types of Data Redundancy
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Interpixel Redundancy:
i. Interpixel redundancy implies that any pixel value can be reasonably predicted by its neighbors (i.e., correlated).
ii. To reduce interpixel redundancy, the data must be transformed in another format (i.e., through a transformation)
Psychovisual Redundancy:
i. The human eye does not respond with equal sensitivity to all visual information.
ii. It is more sensitive to the lower frequencies than to the higher frequencies in the visual spectrum.
iii. Idea: discard data that is perceptually insignificant!
Lossless compression:
1. In lossless compression schemes, the reconstructed image, after compression, is numerically identical to the original image.
2. However lossless compression can only achieve a modest amount of compression.
3. Lossless compression is preferred for archival purposes and often medical imaging, technical drawings, clip art or comics.
4. exploit only data redundancy
Lossy compression:
1. The reconstructed images suffer from blocking artifacts and the image quality will be severely degraded under the circumstance of high compression ratios.
2. The compression will reduce the image fidelity, especially when the images are compressed at lower bit rates.
3. This is because the compression scheme completely discards redundant information.
4. However, lossy schemes are capable of achieving much higher compression.
5. Lossy methods are especially suitable for natural images such as photos in applications where minor (sometimes imperceptible) loss of fidelity is acceptable to achieve a substantial reduction in bit rate.
6. exploit both data redundancy and human perception properties
COMPARISION OF DCT and DWT:
1. DCT is used for transformation in JPEG standard.
2. DCT performs efficiently at medium bit rates.
3. Disadvantage with DCT is that only spatial correlation of the pixels inside the single 2-D block is considered and the correlation from the pixels of the neighboring blocks is neglected. Blocks cannot be decorrelated at their boundaries using DCT.
1. DWT is used as basis for transformation in JPEG 2000 standard.
2. DWT provides high quality compression at low bit rates.
3. The use of larger DWT basis functions or wavelet filters produces blurring near edges in images.
4. DWT performs better than DCT in the context that it avoids blocking artifacts which degrade reconstructed images. However DWT provides lower quality than JPEG at low compression rates.DWT requires longer compression time.