1 June 2002 Adaptive filtering for noise reduction in hue saturation intensity color space
Author Affiliations +
Optical Engineering, 41(6), (2002). doi:10.1117/1.1475996
Even though the hue saturation intensity (HSI) color model has been widely used in color image processing and analysis, the conversion formulas from the RGB color model to HSI are nonlinear and complicated in comparison with the conversion formulas of other color models. When an RGB image is degraded by random Gaussian noise, this nonlinearity leads to a nonuniform noise distribution in HSI, making accurate image analysis more difficult. We have analyzed the noise characteristics of the HSI color model and developed an adaptive spatial filtering method to reduce the magnitude of noise and the nonuniformity of noise variance in the HSI color space. With this adaptive filtering method, the filter kernel for each pixel is dynamically adjusted, depending on the values of intensity and saturation. In our experiments we have filtered the saturation and hue components and generated edge maps from color gradients. We have found that by using the adaptive filtering method, the minimum error rate in edge detection improves by approximately 15%.
Hyun Wook Park, Lakshmanan Gopishankar, Yongmin Kim, "Adaptive filtering for noise reduction in hue saturation intensity color space," Optical Engineering 41(6), (1 June 2002). http://dx.doi.org/10.1117/1.1475996

Digital filtering

RGB color model

Image filtering

Spatial filters

Optical filters

Edge detection

Image analysis


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