Error analysis of 3Dc-based normal map compression and its application to optimized quantization
Normal mapping is one of the most essential technologies for realistic three-dimensional computer graphics. In conventional normal map compression such as 3Dc, only the x and y components are encoded and the z components are restored based on the normalizing condition. In this paper, we present an intuitively comprehensive error analysis for this approach. As a result, we reveal in what condition compression error becomes larger. We also present a non-linear quantization algorithm based on the formula for better compression performance than the conventional approaches. Experimental results using 300 normal map demonstrate that the PSNR is improved by 0.29 dB on average. Our algorithm is compatible with random access and highly-parallel processing on GPU.