Author_Institution :
State Key Lab. of Earth Surface Processes & Resource Ecology, Beijing Normal Univ., Beijing, China
Abstract :
Natural color images are superior to false color images for presentation and visual interpretation purposes. They are widely used in the fields of fly-through of a draped terrain, visual interpretation, and display and have been designed, for example, for nonremote sensing professional users. However, each sensor has its own purpose, application, and limitation. In addition, blue wavelengths suffer the greatest scattering in the atmosphere, which follows an inverse dependence on wavelength to the fourth power. Some of high-resolution satellites cover only two visual spectral bands (green and red bands) plus one in the near-infrared region. As a result, a true color image cannot be formed, as the blue band is necessary in the red, green, and blue combination. This has become problematic for users needing a natural color composite that has limited the application of high-resolution images. To overcome this problem, in this letter, we propose a new approach for generating pseudo natural color (PNC) composite representations from false color composite images based on the spectral similarity scale. The method is validated experimentally. The proposed “natural color generator” can be applied to change false color images into natural color images. The generated PNC images are shown to be of high quality.
Keywords :
geophysical image processing; geophysical techniques; image colour analysis; image representation; image resolution; natural scenes; remote sensing; spectral analysis; blue wavelength; draped terrain; false color composite image; green band; high-resolution image; high-resolution satellite; inverse dependence; natural color generator; near-infrared region; nonremote sensing professional users; pseudonatural color composite representation; pseudonatural color image simulation; red band; spectral similarity scale; true color image; visual display; visual interpretation; visual spectral band; Atmospheric modeling; Color; FCC; Image color analysis; Libraries; Remote sensing; Visualization; Ground-object spectrum; natural color simulation; remote sensing; spectral similarity scale (SSS);