|
About
the Image Coding and Analysis Lab
|
 Research
in the Image Coding and
Analysis Lab broadly
concerns coding and
analysis of visual
information.
We
study topics in image
processing, including
image modeling,
analysis, and
compression, as well as
topics in visual coding
and perception,
including natural scene
statistics and visual
psychophysics.
We are
currently researching
projects in:
-
CSIQ: Categorical
Image Quality
Database
-
New models of
visual masking
based on
classification
-
Automated
region-of-interest
detection and
level-of-interest
estimation
-
Main subject
detection in
images and video
-
Image quality
assessment based
on models of
human vision
-
Estimating the
information
content in
natural scenes
-
Algorithm-architecture
co-design for
model-based
coding
|
Some of our past
work includes:
-
VSNR: A
Wavelet-Based
Visual
Signal-to-Noise
Ratio
-
Visual Detection
and Summation in
Natural Scenes
-
DCQ: Dynamic
Contrast-Based
Quantization for
JPEG-2000
-
Response
Normalization in
Retinal Ganglion
Cells
|
More details on our
research are available
from our
publications.
|
|
|
|
|
|
|
|
|
|
 |
Former lab member Eric
Larson will be
presenting our work on
image quality assessment
titled "Most Apparent
Distortion" at the SPIE:
Image Quality conference
in January 2009. |
|
|
Two research projects
from the Image Coding
and Analysis Lab were
presented at the 2008
International Conference
on Image Processing
(ICIP) in San Diego, CA. |
|
|
|
|
|
|
|
|
|
|
|
|
Copyright © 2004-2008 Image Coding and Analysis Lab. All
Rights Reserved.
