Showing papers on "High-dynamic-range imaging published in 2000"

High dynamic range imaging: spatially varying pixel exposures

Abstract: While real scenes produce a wide range of brightness variations, vision systems use low dynamic range image detectors that typically provide 8 bits of brightness data at each pixel. The resulting low quality images greatly limit what vision can accomplish today. This paper proposes a very simple method for significantly enhancing the dynamic range of virtually any imaging system. The basic principle is to simultaneously sample the spatial and exposure dimensions of image irradiance. One of several ways to achieve this is by placing an optical mask adjacent to a conventional image detector array. The mask has a pattern with spatially varying transmittance, thereby giving adjacent pixels on the detector different exposures to the scene. The captured image is mapped to a high dynamic range image using an efficient image reconstruction algorithm. The end result is an imaging system that can measure a very wide range of scene radiance and produce a substantially larger number of brightness levels, with a slight reduction in spatial resolution. We conclude with several examples of high dynamic range images computed using spatially varying pixel exposures.

Apparatus and method for high dynamic range imaging using spatially varying exposures

Abstract: Apparatus and methods are provided for obtaining high dynamic range images using a low dynamic range image sensor. The scene is exposed to the image sensor in a spatially varying manner. A variable-transmittance mask, which is interposed between the scene and the image sensor, imposes a spatially varying attenuation on the scene light incident on the image sensor. The mask includes light transmitting cells whose transmittance is controlled by application of suitable control signals. The mask is configured to generate a spatially varying light attenuation pattern across the image sensor. The image frame sensed by the image sensor is normalized with respect to the spatially varying light attenuation pattern. The normalized image data can be interpolated to account for image sensor pixels that are either under or over exposed to enhance the dynamic range of the image sensor.

Rendering high dynamic range images

Abstract: In this paper, we review several algorithms that have been proposed to transform a high dynamic range image into a reduced dynamic range image that matches the general appearance of the original. We organize these algorithms into two categories: tone reproduction curves (TRCs) and tone reproduction operators (TROs). TRCs operate pointwise on the image data, making the algorithms simple and efficient. TROs use the spatial structure of the image data and attempt to preserve local image contrast.