Shadow correction in high dynamic range images for generating orthophotos

High dynamic range imagery is widely used in remote sensing. With the widespread use of aerial digital cameras such as the DMC, ADS40, RMK-D, and UltraCamD, high dynamic range imaging is generally expected for generating minuteness orthophotos in digital aerial photogrammetry. However, high dynamic range images (12-bit, 4,096 gray levels) are generally compressed into an 8-bit depth digital image (256 gray levels) owing to huge amount of data and interface with peripherals such as monitors and printers. This means that a great deal of image data is eliminated from the original image, and this introduces a new shadow problem. In particular, the influence of shadows in urban areas causes serious problems when generating minuteness orthophotos and performing house detection. Therefore, shadow problems can be solved by addressing the image compression problems. There is a large body of literature on image compression techniques such as logarithmic compression and tone mapping algorithms. However, logarithmic compression tends to cause loss of details in dark and/or light areas. Furthermore, the logarithmic method intends to operate on the full scene. This means that high-resolution luminance information can not be obtained. Even though tone mapping algorithms have the ability to operate over both full scene and local scene, background knowledge is required. To resolve the shadow problem in digital aerial photogrammetry, shadow areas should be recognized and corrected automatically without the loss of luminance information. To this end, a practical shadow correction method using 12-bit real data acquired by DMC is investigated in this paper.