PVRTC

Abstract: More embedded systems gain increasing multimedia capabilities, including computer graphics. Although this is mainly due to their increasing computational capability, optimizations of algorithms and data structures are important as well, since these systems have to fulfill a variety of constraints and cannot be geared solely towards performance. In this paper, the two most popular texture compression methods (DXT1 and PVRTC) are compared in both image quality and decoding performance aspects. For this, both have been ported to the ePUMA platform which is used as an example of energy consumption optimized embedded systems. Furthermore, a new DXT1 encoder has been developed which reaches higher image quality than existing encoders.

Abstract: A machine may be configured to process an uncompressed image to obtain a set of intermediate images, which may be alternatively known as working images or temporary images. Such a set of intermediate images may be used as input for an image compression algorithm that, when executed by the machine or other compression engine, outputs a compressed version of the uncompressed image. For example, a compression format called “PVRTC,” which may be used on certain portable devices, accepts a set of three intermediate images as input, specifically, one full resolution, low precision version of the original uncompressed image, plus two low resolution, low frequency color versions of the original uncompressed image. A set of intermediate images for such a compression format may be generated by the machine from the original uncompressed image.

Abstract: We present a real-time algorithm for compressing textures based on low frequency signal modulated (LFSM) texture compression. Our formulation is based on intensity dilation and exploits the notion that the most important features of an image are those with high contrast ratios. We present a simple two pass algorithm for propagating the extremal intensity values that contribute to these contrast ratios into the compressed encoding. We use our algorithm to compress PVRTC textures in real-time and compare our performance with prior techniques in terms of speed and quality. http://gamma.cs.unc.edu/FasTC

Abstract: Numerous algorithms have been researched in the area of texture synthesis However, it remains difficult to design a low-cost synthesis scheme capable of generating high quality results while simultaneously achieving real-time performance Additional challenges include making a scheme parallel and being able to partially render/synthesize high-resolution textures Furthermore, it would be beneficial for a synthesis scheme to be able to incorporate Texture Compression and minimize the bandwidth usage, especially on mobile devices In this paper, we propose a practical method which has low computational complexity and produces textures with small storage requirements Through use of an index table, random access of the texture is another essential advantage, with which parallel rendering becomes feasible including generation of mip-map sequences Integrating the index table with existing compression algorithms, for example ETC or PVRTC, the bandwidth is further reduced and avoids the need for a separate, computationally expensive pass to compress the synthesized output It should be noted that our texture synthesis achieves real-time performance and low power consumption even on mobile devices, for which texture synthesis has been traditionally considered too expensive