1 / 15

JPEG 2000 Image Analysis

JPEG 2000 Image Analysis. Darius Fennell University of Rochester. Experiment Objective. Using JPEG 2000 calculate and analyze the following: Distortion vs. Rate Distortion vs. Quantization Time vs. Quantization Time vs. Resolution. Experiment Materials. Dell Computer 2.79 GHz Processing

race
Download Presentation

JPEG 2000 Image Analysis

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. JPEG 2000 Image Analysis Darius Fennell University of Rochester

  2. Experiment Objective • Using JPEG 2000 calculate and analyze the following: • Distortion vs. Rate • Distortion vs. Quantization • Time vs. Quantization • Time vs. Resolution

  3. Experiment Materials • Dell Computer • 2.79 GHz Processing • 2.00 GB of RAM • Matlab 7.0.1 R14 • Kakadu JPEG 2000 software • 5 Standard images

  4. Standard Imagery • Originally 3 bands @ 512x512 • Reduced to single band 128x128

  5. Basic JPEG 2000 Compression Chain

  6. Expectation • Distortion vs. Rate • As rate increases distortion decreases • Distortion vs. Quantization • As step size decreases distortion decreases • Time vs. Quantization • As quantization increases time decreases • Time vs. Spatial Resolution • As Spatial Resolution increases time increases

  7. Distortion vs. Rate • Imagery compressed at multiple rates: • 7.0,4.0,2.0,1.0,0.5, and 0.25 • Average Bit Rate per pixel • Imagery decompressed to each rate and compared to the original. • MSE=var(original-decompressed)

  8. Distortion vs. Rate Results

  9. Quantization • Imagery compressed using varying step sizes:2^-7 to 2^7 • MSE calculated • Processing time determined by Matlab’s tic/toc command

  10. Distortion vs. Quantization Results

  11. Time vs. Quantization Results

  12. Time vs. Spatial Resolution • Images Sizes: • 512x512 • 256x256 • 128x128 • 64x64 • Processing time determined by Matlab’s tic/toc command

  13. Time vs. Spatial Resolution

  14. Conclusion • Rate & quantization have a drastic effect on the error. • Step size does not significantly effect compression time for quantization. • Increased spatial resolution increases compression time yet other factors are involved that affect the over processing chain.

  15. References • http://www.kakadusoftware.com • http://www.gvsu.edu/math/wavelets/student_work/EF/index.html

More Related