Name
Abstract | ||
|---|---|---|
Histogram specification has been successfully used in digital image processing over the years. Mainly used as an image enhancement technique, methods such as histogram equalization (HE) can yield good contrast with almost no effort in terms of inputs to the algorithm or the computational time required. More elaborate histograms can take on problems faced by HE at the expense of having to define the final histograms in innovative ways that may require some extra processing time but are nevertheless fast enough to be considered for real-time applications. This paper proposes a new technique for specifying a histogram to enhance the image contrast. To further evidence our faith on histogram specification techniques, we also discuss methods to modify images, e.g., to help segmentation approaches. Thus, as advocates of these techniques, we would like to emphasize the flexibility of this image processing approach to do more than enhancing images. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/TIM.2010.2089110 | Instrumentation and Measurement, IEEE Transactions |
Keywords | Field | DocType |
image enhancement,image segmentation,maximum entropy methods,digital image processing,histogram specification,image contrast,image enhancement technique,maximum entropy,Contrast enhancement,histogram equalization (HE),histogram specification (HS),maximum entropy,segmentation | Normalization (image processing),Computer vision,Pattern recognition,Image processing,Histogram matching,Adaptive histogram equalization,Artificial intelligence,Balanced histogram thresholding,Image histogram,Histogram equalization,Color normalization,Mathematics | Journal |
Volume | Issue | ISSN |
60 | 5 | 0018-9456 |
Citations | PageRank | References |
14 | 0.65 | 8 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Gabriel Thomas | 1 | 49 | 9.23 |
| Daniel Flores-Tapia | 2 | 32 | 4.36 |
| Stephen Pistorius | 3 | 22 | 4.75 |