Uniform frequency images: adding geometry to images to produce space-efficient textures

Discusses the concept of uniform frequency images, which exhibit uniform local frequency properties. Such images make optimal use of space when sampled close to their Nyquist limit. A warping function may be applied to an arbitrary image to redistribute its local frequency content, reducing its highest frequencies and increasing its lowest frequencies in order to approach this uniform frequency ideal. The warped image may then be downsampled according to its new, reduced Nyquist limit, thereby reducing its storage requirements. To reconstruct the original image, the inverse warp is applied. We present a general, top-down algorithm to automatically generate a piecewise-linear warping function with this frequency balancing property for a given input image. The image size is reduced by applying the warp and then downsampling. We store this warped, downsampled image plus a small number of polygons with texture coordinates to describe the inverse warp. The original image is later reconstructed by rendering the associated polygons with the warped image applied as a texture map, a process which is easily accelerated by current graphics hardware. As compared to previous image compression techniques, we generate a similar graceful space-quality tradeoff with the advantage of being able to "uncompress" images during rendering. We report results for several images with sizes ranging from 15,000 to 300,000 pixels, achieving reduction rates of 70-90% with improved quality over downsampling alone.