Abstract: An exposure correction method for digital images first computes a gray-level histogram of an image. Then determine whether the exposure of the image is normal from the gray-level histogram, thereby determining an exposure threshold. The central region of the image is extracted to find an average brightness Iave. The average brightness Iave and a destination brightness Idest are used to determine an adjusting curve y=f(x). The brightness channel is adjusted according to a constructed correspondence table. Therefore, the image processing effects are enhanced even though the processing time is reduced.

Abstract: In a method of processing red eye in digital images, a skin area is first determined in an image. Then all inner boundaries within the skin area are picked up. The inner boundaries are matched with an eyelid quadratic curve to determine the location of the eyelid area. Red pixels within the eyelid area are then detected and filled up. A quadratic curve model can be further used to localize an iris area within the eyelid area to improve the precision of red eye localization as well as the processing speed.

Abstract: An exposure correction method for digital images first computes a gray-level histogram of an image. Then determine whether the exposure of the image is normal from the gray-level histogram, thereby determining an exposure threshold. The central region of the image is extracted to find an average brightness Iave. The average brightness Iave and a destination brightness Idest are used to determine an adjusting curve y=f(x). The brightness channel is adjusted according to a constructed correspondence table. Therefore, the image processing effects are enhanced even though the processing time is reduced.

Abstract: In a method of processing red eye in digital images, a skin area is first determined in an image. Then all inner boundaries within the skin area are picked up. The inner boundaries are matched with an eyelid quadratic curve to determine the location of the eyelid area. Red pixels within the eyelid area are then detected and filled up. A quadratic curve model can be further used to localize an iris area within the eyelid area to improve the precision of red eye localization as well as the processing speed.