Jon Hasselgren

Stochastic rasterization using time-continuous triangles

We present a novel algorithm for stochastic rasterization which can rasterize triangles with attributes depending on a parameter, t, varying continuously from t = 0 to t = 1 inside a single frame. These primitives are called time-continuous triangles, and can be used to render motion blur. We develop efficient techniques for rasterizing time-continuous triangles, and specialized sampling and filtering algorithms for improved image quality. Our algorithm needs some new hardware mechanisms implemented on top of todays graphics hardware pipelines. However, our algorithm can leverage much of the already existing hardware units in contemporary GPUs, which makes the implementation fairly inexpensive. We introduce time-dependent textures, and show that motion blurred shadows and motion blurred reflections can be handled in our framework. In addition, we also present new techniques for efficient rendering of depth of field and glossy planar reflections using our stochastic rasterizer.

High dynamic range texture compression for graphics hardware

In this paper, we break new ground by presenting algorithms for fixed-rate compression of high dynamic range textures at low bit rates. First, the S3TC low dynamic range texture compression scheme is extended in order to enable compression of HDR data. Second, we introduce a novel robust algorithm that offers superior image quality. Our algorithm can be efficiently implemented in hardware, and supports textures with a dynamic range of over 109:1. At a fixed rate of 8 bits per pixel, we obtain results virtually indistinguishable from uncompressed HDR textures at 48 bits per pixel. Our research can have a big impact on graphics hardware and real-time rendering, since HDR texturing suddenly becomes affordable.In this paper, we break new ground by presenting algorithms for fixed-rate compression of high dynamic range textures at low bit rates. First, the S3TC low dynamic range texture compression scheme ...

Adaptive enhancement and noise reduction in very low light-level video

A general methodology for noise reduction and contrast enhancement in very noisy image data with low dynamic range is presented. Video footage recorded in very dim light is especially targeted. Smoothing kernels that automatically adapt to the local spatio-temporal intensity structure in the image sequences are constructed in order to preserve and enhance fine spatial detail and prevent motion blur. In color image data, the chromaticity is restored and demosaicing of raw RGB input data is performed simultaneously with the noise reduction. The method is very general, contains few user-defined parameters and has been developed for efficient parallel computation using a GPU. The technique has been applied to image sequences with various degrees of darkness and noise levels, and results from some of these tests, and comparisons to other methods, are presented. The present work has been inspired by research on vision in nocturnal animals, particularly the spatial and temporal visual summation that allows these animals to see in dim light.

Efficient depth buffer compression

Depth buffer performance is crucial to modern graphics hardware. This has led to a large number of algorithms for reducing the depth buffer bandwidth. Unfortunately, these have mostly remained documented only in the form of patents. Therefore, we present a survey on the design space of efficient depth buffer implementations. In addition, we describe our novel depth buffer compression algorithm, which gives very high compression ratios.

PCU: the programmable culling unit

Culling techniques have always been a central part of computer graphics, but graphics hardware still lack efficient and flexible support for culling. To improve the situation, we introduce the programmable culling unit, which is as flexible as the fragment program unit and capable of quickly culling entire blocks of fragments. Furthermore, it is very easy for the developer to use the PCU as culling programs can be automatically derived from fragment programs containing a discard instruction. Our PCU can be integrated into an existing fragment program unit with a modest hardware overhead of only about 10%. Using the PCU, we have observed shader speedups between 1.4 and 2.1 for relevant scenes.

HMS: a predictive text entry method using bigrams

Due to the emergence of SMS messages, the significance of effective text entry on limited-size keyboards has increased. In this paper, we describe and discuss a new method to enter text more efficiently using a mobile telephone keyboard. This method, which we called HMS, predicts words from a sequence of keystrokes using a dictionary and a function combining bigram frequencies and word length. We implemented the HMS text entry method on a software-simulated mobile telephone keyboard and we compared it to a widely available commercial system. We trained the language model on a corpus of Swedish news and we evaluated the method. Although the training corpus does not reflect the language used in SMS messages, the results show a decrease by 7 to 13 percent in the number of keystrokes needed to enter a text. These figures are very encouraging even though the implementation can be optimized in several ways. The HMS text entry method can easily be transferred to other languages.

An efficient multi-view rasterization architecture

TV have been designed and built. However, these displays have received relatively little attention in the context of real-time computer graphics. We present a novel rasterization architecture that rasterizes each triangle to multiple views simultaneously. When determining which tile in which view to rasterize next, we use an efficiency measure that estimates which tile is expected to get the most hits in the texture cache. Once that tile has been rasterized, the efficiency measure is updated, and a new tile and view are selected. Our traversal algorithm provides significant reductions in the amount of texture fetches, and bandwidth gains on the order of a magnitude have been observed. We also present an approximate rasterization algorithm that avoids pixel shader evaluations for a substantial amount (up to 95%) of fragments and still maintains high image quality.

Automatic pre-tessellation culling

Graphics processing units supporting tessellation of curved surfaces with displacement mapping exist today. Still, to our knowledge, culling only occurs after tessellation, that is, after the base primitives have been tessellated into triangles. We introduce an algorithm for automatically computing tight positional and normal bounds on the fly for a base primitive. These bounds are derived from an arbitrary vertex shader program, which may include a curved surface evaluation and different types of displacements, for example. The obtained bounds are used for backface, view frustum, and occlusion culling before tessellation. For highly tessellated scenes, we show that up to 80% of the vertex shader instructions can be avoided, which implies an “instruction speedup” of 5×. Our technique can also be used for offline software rendering.

Exact and error-bounded approximate color buffer compression and decompression

In this paper, we first present a survey of existing color buffer compression algorithms. After that, we introduce a new scheme based on an exactly reversible color transform, simple prediction, and Golomb-Rice encoding. In addition to this, we introduce an error control mechanism, which can be used for approximate (lossy) color buffer compression. In this way, the introduced error is kept under strict control. To the best of our knowledge, this has not been explored before in the literature. Our results indicate superior compression ratios compared to existing algorithms, and we believe that approximate compression can be important for mobile GPUs.

Coarse pixel shading

We present a novel architecture for flexible control of shading rates in a GPU pipeline, and demonstrate substantially reduced shading costs for various applications. We decouple shading and visibility by restricting and quantizing shading rates to a finite set of screen-aligned grids, leading to simpler and fewer changes to the GPU pipeline compared to alternative approaches. Our architecture introduces different mechanisms for programmable control of the shading rate, which enables efficient shading in several scenarios, e.g., rendering for high pixel density displays, foveated rendering, and adaptive shading for motion and defocus blur. We also support shading at multiple rates in a single pass, which allows the user to compute different shading terms at rates better matching their frequency content.