A Comparison of Quality Metrics for JPEG Images
  
                 ---EE368b Final Project Proposal

                          Feng Xiao

Blocking artifact is the most obvious artifact associated with JPEG
(or other block-based coding), especially at very low bit rate. Some
post-processing methods have been proposed to reduce this annoy artifact
by smoothing, which, unfortunately, will incur blurring artifact.
Different implementations may use different strategy to balance the trade
off. To compare the performance of different implementations, we need to
find a way to evaluate the distortion in processed image. 

Subjective tests are the most reliable but they are too time-consuming
for wide application. Although criticized for not taking into account of
the property of human vision system (HVS), MSE and its inherences (PSNR
or so) are still the dominant objective image quality metrics. Many other
objective image quality metrics, which imitate more or less of HVS have
been proposed. 

Since blocking and blurring are the dominant artifacts in JPEG, it will
be very helpful if we can find a better objective distortion metrics that
is more closely related to our subjective impression of blocking and
blurring artifacts. In this project, I will compare the correlations
between several objective quality metrics and subjective experience.
Candidate metrics are:

   1.      PSNR (or MSE)

   2.      Liu's blocking and blurring metrics

   3.      Eskicioglu's blocking metrics

   4.      Watson's DCTune

References:

   1.Ahumada,A.J. Jr. (1993).Computational Image Quality Metrics: A Review,
     Society for Information Display
     International Symposium, Digest of Technical Papers, 24, 305-308.

   2.Eskicioglu,A.M & Fisher P.S. (1995). Image quality measures and their
     performance. IEEE Transactions on Communications. 43(12), 2959-2965.

   3.Liu,C.M., Lin,J.Y., Wu,K.G. & Wang,C.N. (1997). Objective image quality
     measure for block-based DCT coding.
     IEEE Transactions on Consumer Electronics. 43(3), 511-516.

   4.Rohaly,A.M. et al. (2000). Video Quality Experts Group: current results
     and future directions. http://www.crc.ca/vqeg/