The Study Of Adaptive Sampling Algorithm Using Combinaion Measurement

There are two goals for realistic image synthesis technology. One is to produce pictures that exactly like a photo produced by a cammare; It can simulate all kinds of illuminating conditions and guarantee a realistic result. The other is to gain a balance between the image quality and computation price. We want good images as less computation as possible. We dedicate to the second goal. One preferable chosen is the adaptive sampling technology. The adaptive sampling technology can distribute computation according to the quality of different areas in image plane. After a low sample rate, we get a low quality image. The method can find where the quality is not enough, and add samples to the area. The key to the adaptive sampling technology is a good measurement of pixel quality.Besides the adaptive sampling technology, progressive rendering also needs a balance between the image quality and computation price. We introduce the konwdege about adaptive sampling, quality measurement, and a classic progressive rendering technology. We get inspiration from the konwdege and prompt our own quality measurement, and practice it in adaptive sampling technology frame. We also change the control flow and replace it with a quadtree from the original image plane. We study all spects of the performance of the new algorithm by experiments. We compare the RMS of the result image and the standard image produced by heavily sampling. The RMS and the corresponding average sampling number denote the performance of the algorithm. We compare the algorithm with the classic contracted based adaptive sampling in the way. We study the advantages and the shortages. At last we propose advices for the development of the algorithm.