First, the images captured and displayed by photographic and electronic cameras suffer from a comparative loss of detail and color in shadowed zones. This is known as the dynamic range problem.

 

	Second, the images are subject to color distortions when the spectral distribution of the illuminant changes. This is known as the color constancy problem. A commonly encountered instance of the color constancy problem is the spectral difference between daylight and artificial (e.g., tungsten) light which is sufficiently strong to require photographers to shift to some combination of film, filters and processing to compensate for the spectral shift in illumination. Though film photographers can attempt to approximately match film type to spectral changes in lighting conditions, digital cameras must rely strictly on filters. However, these methods of compensation do not provide any dynamic range compression thereby causing detail and color in shadows to be lost or severely attenuated compared to what a human observer would actually see.
	For non-color imaging including non-optical imaging, the problem becomes simpler and is largely one of dynamic range compression, i.e., the capture and representation of detail and lightness values across wide ranging average signal levels that can vary dramatically across a scene. Electronic cameras based upon CCD detector arrays are quite capable of acquiring image data across a wide dynamic range on the order to 2500:1. This range is suitable for handling most illumination variations within scenes, and lens aperture changes are usually employed to encompass scene-to-scene illumination variations. Typically though, this dynamic range is lost when the image is digitized or when the much narrower dynamic range of print and display media are encountered. For example, most images are digitized to 8-bits/color band (256 gray levels/color band) and most display and print media are even more limited to a 50:1 dynamic range.
	Another problem encountered in color and non-color image processing is known as color/lightness rendition. This problem results from trying to match the processed image with what is observed and consists of 1) lightness and color halo artifacts that are especially prominent where large uniform regions of an image abut to form a high contrast edge with graying in the large uniform zones, and 2) global violations of the gray world assumption (e.g., an all-red scene) which results in a global graying out of the image.