Name
Abstract | ||
|---|---|---|
We propose a method for improving the accuracy of histogram-based image filtering. With this method, we define a histogram called intensity-stacked histogram. An image histogram generally consists of a frequency (number of pixels) for each bin. On the other hand, intensity-stacked histogram stores the sum of intensity values for each bin. The intensity-stacked histogram can be calculated in constant time similar to a standard histogram. We apply the intensity-stacked histogram to histogram-based image algorithms for median and bilateral filters. The histogram-based image filter with the intensity-stacked histogram works effectively when using a few bins. We confirmed that the accuracy of histogram-based image filters using intensity-stacked histogram is higher than that using standard histogram. |
Year | Venue | Keywords |
|---|---|---|
2013 | 2013 20TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP 2013) | Image filter, local histogram, median filter, bilateral filter, intensity-stacked histogram |
Field | DocType | ISSN |
Histogram,Computer vision,Pattern recognition,Color histogram,Computer science,Histogram matching,Adaptive histogram equalization,Artificial intelligence,Balanced histogram thresholding,Histogram equalization,Image histogram,Color normalization | Conference | 1522-4880 |
Citations | PageRank | References |
3 | 0.43 | 5 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Masaki Igarashi | 1 | 5 | 0.83 |
| Akira Mizuno | 2 | 6 | 6.03 |
| M. Ikebe | 3 | 47 | 13.63 |