Name
Title | ||
|---|---|---|
Iterative exact global histogram specification and SSIM gradient ascent: a proof of convergence, step size and parameter selection |
Abstract | ||
|---|---|---|
The SSIM-optimized exact global histogram specification (EGHS) is shown to
converge in the sense that the first order approximation of the result's
quality (i.e., its structural similarity with input) does not decrease in an
iteration, when the step size is small. Each iteration is composed of SSIM
gradient ascent and basic EGHS with the specified target histogram. Selection
of step size and other parameters is also discussed. |
Year | Venue | Keywords |
|---|---|---|
2010 | Clinical Orthopaedics and Related Research | pattern recognition,first order,structural similarity |
DocType | Volume | Citations |
Journal | abs/1002.3 | 0 |
PageRank | References | Authors |
0.34 | 2 | 1 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Alireza Nasiri Avanaki | 1 | 48 | 8.82 |