Friday, 10 January 2014

Comparison between SPIHT and Advanced SPIHT with Huffman coding.....Experimental Results.


Quality Parameters 
1. Mean Square Error
Two commonly used measures for quantifying the error between images are Mean Square Error (MSE) and Peak Signal to Noise Ratio (PSNR). The MSE between two images I and K is denoted by


Where m is number of rows and n is number of columns present in an image.
2. Compression Ratio:
The compression ratio is calculated as the ratio of number of bits required to represent original image to the number of bits required to represent compressed codestream.
3. Peak-Signal to Noise Ratio (PSNR):
The PSNR is most commonly used as a measure of quality of reconstruction of lossy compression codec’s (e.g., for image compression). The signal in this case is the original data, and the noise is the error introduced by compression. When comparing compression codec’s it is used as an approximation to human perception of reconstruction quality, therefore in some cases one reconstruction may appear to be closer to the original than another, even though it has a lower PSNR (a higher PSNR would normally indicate that the reconstruction is of higher quality). The PSNR is calculated by using following formula.

4. Average Difference (AD):
Average difference of an image is given by a formula as below
Large value of AD means that the pixel values in reconstructed images are more deviated from actual pixel value. Large value of AD indicates image is of poor quality. 

5. Structural Content (SC):
Structural content of an image is given by the formula as below

Large the Structural Content, image is of poor quality.

Detailed implementation of SPIHT and Advanced SPIHT you can see here
Screen shots of GUI Implementation of both SPIHT and Advanced SPIHT is as follows

Main GUI window

MATLAB Implementation of SPIHT Compression and Decompression 
MATLAB Implementation of Advanced SPIHT Compression and Decompression 
Comparison Result with GUI


Experimental Results for Lena Image:







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2 comments:

  1. hello sir, you have done impressive work in this project.I am interested in this project.Please send me the matlab code at my email id goelvikas545@gmail.com

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