In texture mapping, anisotropic filtering methods, which require more texels, have been proposed for high-quality images. Memory bandwidth, however, is still limited by a bottleneck in the texture-filtering hardware. In this paper, we propose anisotropic texture filtering based on edge function. In generating the weight that plays a key role in filtering texels loaded from memory, the edge function gives accurate contribution of texels to the pixel intensity. The quality of images is superior to other methods. For images of the same quality, our method requires less than half the texels of other methods. In other words, the improvement in performance is more than twice that of other methods.

In this paper, a fragment-processing solution in 3D graphics rendering algorithms based on fragment lists (i.e. A-buffer) for minimizing loss of image quality is described. While all fragment information should be preserved for exact hidden surface removal, this places additional strain on hardware in terms of silicon gates and clock cycles. Therefore, we propose a fragment processing technique that can effectively merge fragments in order to decrease the depth of fragment lists. It renders scenes quite accurately even in the case when three fragments intersect each other. This algorithm improves hardware acceleration without deteriorating image quality.

The PN triangle method has a great significance in processing tessellation at the hardware level without software assistance. Despite its significance, however, the conventional PN triangle method has certain defects such as inefficient GE operation and degradation of visual quality. Because the method tessellates a curved surface according to the user-defined fixed LOD (Level Of Detail). In this paper, we propose adaptive tessellation of PN triangles using minimum-artifact edge linking. Through this method, higher efficiency of tessellation and better quality of scene are obtained by adaptivity and minimum-artifact edge linking, respectively. This paper also presents a hardware architecture of a PN triangle method using adaptive LOD, which is not a burden for overall 3D graphics hardware.

This paper proposes a new binary motion estimation algorithm that improves the motion vector accuracy by using a hybrid distortion measure. Unlike conventional binary motion estimation algorithms, the proposed algorithm considers the sum of absolute difference (SAD) as well as the sum of bit-wise difference (SBD) as a block-matching criterion. In order to reduce the computational complexity and remove additional memory accesses, a new scheme is used for SAD calculation. This scheme uses 8-bit data of the lowest layer already moved into the local buffer to calculate the SAD of other higher binary layer. Experimental results show that the proposed algorithm finds more accurate motion vectors and removes the blockishness of the reconstructed video effectively. We applied this algorithm to existing video encoder and obtained noticeable visual quality enhancement.

Antialiased is one of challenging problems to be solved for the high fidelity image synthesis in 3D graphics. In this paper a rasterization processor which is capable of single-pass full-screen antialiasing is presented. To implement a H/W accelerated single-pass antialiased rasterization processor at the reasonable H/W cost and minimized processing performance degradation, our work is mainly focused on the efficient H/W implementation of a modified version of the A-buffer algorithm. For the efficient handling of partial-pixel fragments of the rasterization phase, a new partial-pixel-merging scheme and a simple and efficient new dynamic memory management scheme are proposed. For the final blending of partial-pixels without loss of generality, a parallel subpixel blender is introduced. To study the feasibility of the proposed rasterization processor as a practical rasterization processor, a prototype processor has been designed using a 0.35 µm EML technology. It operates 100 MHz @3.3 V and has the rendering performance from 25M to 80M pixel-fragments/sec depending on the scene complexity.

A motion refinement algorithm is proposed to enhance motion compensated noise reduction (MCNR) efficiency. Instead of the vector with minimum distortion, the vector with minimum distance from motion vectors of neighboring blocks is selected as the best motion vector among vectors which have distortion values within the range set by noise level. This motion refinement finds more accurate motion vectors in the noisy sequences. The MCNR with the proposed algorithm maintains the details of an image sequence very well without blurring and joggling. And it achieves 10% bit-usage reduction or 0.5 dB objective quality enhancement in subsequent video coding.