HDR Image Synthesis Based on Multi-exposure Color Images
In digital camera, it’s difficult to exceed the dynamic range of 60~80dB because of the saturation current and background noise of CCD/CMOS image sensor in a single exposure image. In order to obtain more information and detail of a scene, we should extend its dynamic range, which was called HDR technology. Recent years, HDR imaging techniques have become the focus of much research because of their high theoretical and practical importance. By applying HDR techniques, the performance of different image processing and computer vision algorithms, information enhancement, and object and pattern recognition can also be improved. In this paper, a new tone reproduction algorithm is introduced, based on which may help to develop the hard-to-view or nonviewable features and details of color images. This method applies on multi-exposure images synthesis technique, where the red, green, and blue (RGB) color components of the pixels are separately handled. In the output, the corresponding (modified) color components are blended. As a result, a high quality HDR image is obtained, which contains almost the whole details and color information.
Keywordscolor image processing high dynamic range (HDR) image image enhancement multi-exposure images synthesize
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- 3.Várkonyi-Kóczy, A.R.: Improved fuzzy logic supported HDR colored information enhancement. In: I2MTC-International Instrumentation and Measurement Technology Conference, Singapore, pp. 361–366 (2009)Google Scholar
- 5.Russo, F.: Fuzzy filtering of noisy sensor data. In: Proc. of the IEEE Instrumentation and Measurement Technology Conference, Brussels, Belgium, pp. 1281–1285 (1996)Google Scholar
- 7.Adelson, E.H., Pentland, A.P.: The Perception of Shading and Reflectance. In: Knill, D., Richards, W. (eds.) Perception as Bayesian Inference, pp. 409–423. Cambridge University Press, New York (1996)Google Scholar
- 8.Rovid, A., Varlaki, P.: Method for Merging Multiple Exposure Color Image Data. In: International Conference on Intelligent Engineering Systems, pp. 27–31 (2009)Google Scholar