Adaptive Scalable Texture Compression
About: Adaptive Scalable Texture Compression is a research topic. Over the lifetime, 197 publications have been published within this topic receiving 4317 citations.
Papers published on a yearly basis
••01 Jul 2000
TL;DR: This paper presents an efficient algorithm for realistic texture synthesis derived from Markov Random Field texture models and generates textures through a deterministic searching process that accelerates this synthesis process using tree-structured vector quantization.
Abstract: Texture synthesis is important for many applications in computer graphics, vision, and image processing. However, it remains difficult to design an algorithm that is both efficient and capable of generating high quality results. In this paper, we present an efficient algorithm for realistic texture synthesis. The algorithm is easy to use and requires only a sample texture as input. It generates textures with perceived quality equal to or better than those produced by previous techniques, but runs two orders of magnitude faster. This permits us to apply texture synthesis to problems where it has traditionally been considered impractical. In particular, we have applied it to constrained synthesis for image editing and temporal texture generation. Our algorithm is derived from Markov Random Field texture models and generates textures through a deterministic searching process. We accelerate this synthesis process using tree-structured vector quantization.
TL;DR: This article describes a simple general-purpose data compression algorithm, called Byte Pair Encoding (BPE), which provides almost as much compression as the popular Lempel, Ziv, and Welch method.
Abstract: Data compression is becoming increasingly important as a way to stretch disk space and speed up data transfers. This article describes a simple general-purpose data compression algorithm, called Byte Pair Encoding (BPE), which provides almost as much compression as the popular Lempel, Ziv, and Welch (LZW) method [3, 2]. (I mention the LZW method in particular because it delivers good overall performance and is widely used.) BPE’s compression speed is somewhat slower than LZW’s, but BPE’s expansion is faster. The main advantage of BPE is the small, fast expansion routine, ideal for applications with limited memory. The accompanying C code provides an efficient implementation of the algorithm.
TL;DR: A compression algorithm is developed that exploits a new adaptive basis of functions which is reasonably well localized with only one peak in frequency to obtain the most economical representation of the image in terms of textured patterns with different orientations, frequencies, sizes, and positions.
••01 Aug 1996
TL;DR: A simple method for rendering directly from compressed textures in hardware and software rendering systems, with minimal loss in visual quality and a small impact on rendering time is presented.
Abstract: We present a simple method for rendering directly from compressed textures in hardware and software rendering systems. Textures are compressed using a vector quantization (VQ) method. The advantage of VQ over other compression techniques is that textures can be decompressed quickly during rendering. The drawback of using lossy compression schemes such as VQ for textures is that such methods introduce errors into the textures. We discuss techniques for controlling these losses. We also describe an extension to the basic VQ technique for compressing mipmaps. We have observed compression rates of up to 35 : 1, with minimal loss in visual quality and a small impact on rendering time. The simplicity of our technique lends itself to an efficient hardware implementation. CR categories: I.3.7 [Computer Graphics]: 3D Graphics and Realism Texture; I.4.2 [Image Processing]: Compression Coding
••30 Jul 2005
TL;DR: This work presents a novel texture compression scheme, called iPACKMAN, targeted for hardware implementation, which outperforms the previous de facto standard texture compression algorithms in the majority of all cases that it has tested.
Abstract: We present a novel texture compression scheme, called iPACKMAN, targeted for hardware implementation. In terms of image quality, it outperforms the previous de facto standard texture compression algorithms in the majority of all cases that we have tested. Our new algorithm is an extension of the PACKMAN texture compression system, and while it is a bit more complex than PACKMAN, it is still very low in terms of hardware complexity.
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