19-01-2013, 02:55 PM
Discrete Wavelet Transform (DWT)
Discrete Wavele.ppt (Size: 801.5 KB / Downloads: 329)
Need for Compression
Transmission and storage of uncompressed video would be extremely costly and impractical.
Frame with 352x288 contains 202,752 bytes of information
Recoding of uncompressed version of this video at 15 frames per second would require 3 MB. One minute180 MB storage. One 24-hour day262 GB
Using compression, 15 frames/second for 24 hour1.4 GB, 187 days of video could be stored using the same disk space that uncompressed video would use in one day
Principles of Compression
Spatial Correlation
Redundancy among neighboring pixels
Spectral Correlation
Redundancy among different color planes
Temporal Correlation
Redundancy between adjacent frames in a sequence of image
Classification of Compression
Lossless vs. Lossy Compression
Lossless
Digitally identical to the original image
Only achieve a modest amount of compression
Lossy
Discards components of the signal that are known to be redundant
Signal is therefore changed from input
Achieving much higher compression under normal viewing conditions no visible loss is perceived (visually lossless)
Predictive vs. Transform coding
Discrete Wavelet Transform
The wavelet transform (WT) has gained widespread acceptance in signal processing and image compression.
Because of their inherent multi-resolution nature, wavelet-coding schemes are especially suitable for applications where scalability and tolerable degradation are important
Recently the JPEG committee has released its new image coding standard, JPEG-2000, which has been based upon DWT.
Integer DWT
A more efficient approach to lossless compression
Whose coefficients are exactly represented by finite precision numbers
Allows for truly lossless encoding
IWT can be computed starting from any real valued wavelet filter by means of a straightforward modification of the lifting schema
Be able to reduce the number of bits for the sample storage (memories, registers and etc.) and to use simpler filtering units.
Disadvantages of DCT
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
Impossible to completely decorrelate the blocks at their boundaries using DCT
Undesirable blocking artifacts affect the reconstructed images or video frames. (high compression ratios or very low bit rates)
Advantages of DWT over DCT
No need to divide the input coding into non-overlapping 2-D blocks, it has higher compression ratios avoid blocking artifacts.
Allows good localization both in time and spatial frequency domain.
Transformation of the whole image introduces inherent scaling
Better identification of which data is relevant to human perception higher compression ratio
Future video/image compression
Improved low bit-rate compression performance
Improved lossless and lossy compression
Improved continuous-tone and bi-level compression
Be able to compress large images
Use single decompression architecture
Transmission in noisy environments
Robustness to bit-errors
Progressive transmission by pixel accuracy and resolution
Protective image security