Dynamic Range Compression & Color Constancy Democritus University of Thrace 2006 2006.

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Presentation transcript:

Dynamic Range Compression & Color Constancy Democritus University of Thrace

Dynamic Range: The ratio between the maximum and the minimum tonal values in an image (cd/m 2 ) Commercial cameras have only a dynamic range of 256:1 (the maximum value is 256 times greater than the minimum value that they can capture) Scenes with grater dynamic range than 256:1 are not captured correctly (intensities are clipped) Dynamic Range

The dynamic range of natural scenes is a lot more than 256:1(object in frond of a backlight) The camera can capture correctly only the bright or the dark area, but never both of them (underexposure, overexposure) The Dynamic Range Problem Underexposured (no visible details) Normaly exposured Overexposured (no visible details) Normaly exposured

Images with dynamic range problem

Our approach –center surround surround center Center Surround Every pixel (center) is compared with its neighborhood (surround) and is assigned a new value, in order to maximize the contrast in the dark regions of the image Surround is the average intensity value of the neighborhood (0-255) Center is the intensity of the pixel (0-255)

Center-surround transfer function Center Surround In a dark image region (surround is small) When the center is dark Before: Surround 18 Center 23 After: Surround 18 Center 85 18

Center-surround transfer function Center Surround In a dark image region (surround is small) When the center is bright Before: Surround 18 Center 241 After: Surround 18 Center

Center-surround transfer function Center Surround In a bright image region (surround is high) When the center is dark 36 Before: Surround 240 Center 36 After: Surround 240 Center

Center-surround transfer function Center Surround In a bright image region (surround is high) When the center is bright 244 Before: Surround 240 Center 244 After: Surround 240 Center

Conclusion Center Surround In a dark image region (shadows or underexposured areas) the value of the pixel is increased relatively its neighborhood, increasing the local contrast In a bright image region (normally exposured areas) the value of the pixel is unchangeable

Results

The unknown illuminant problem white The HVS has a degree of color constancy

Images under color illuminant Incandescent lights Green water Fluorescent light

The specularity problem Specularities and direct light sources have a greater intensity than the response to pure white Which intensity is the response to pure white?

Our approach: estimate the white response

Results