10 research outputs found
Image Sampling with Quasicrystals
We investigate the use of quasicrystals in image sampling. Quasicrystals
produce space-filling, non-periodic point sets that are uniformly discrete and
relatively dense, thereby ensuring the sample sites are evenly spread out
throughout the sampled image. Their self-similar structure can be attractive
for creating sampling patterns endowed with a decorative symmetry. We present a
brief general overview of the algebraic theory of cut-and-project quasicrystals
based on the geometry of the golden ratio. To assess the practical utility of
quasicrystal sampling, we evaluate the visual effects of a variety of
non-adaptive image sampling strategies on photorealistic image reconstruction
and non-photorealistic image rendering used in multiresolution image
representations. For computer visualization of point sets used in image
sampling, we introduce a mosaic rendering technique.Comment: For a full resolution version of this paper, along with supplementary
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Interactive Contrast Enhancement by Histogram Warping
We present an interactive contrast enhancement technique for the global histogram modification of images. Through direct manipulation, the user adjusts contrast by clicking on the image. Contrast around different key tones can be adjusted simultaneously and independently without altering their luminance. Histogram warping by monotonic splines performs the gray level mapping. User interfaces for contrast correction find application in digital photography, remote sensing, medical imaging, and scientific visualization
Stylized Rendering for Multiresolution Image Representation
By integrating stylized rendering with an efficient multiresolution image representation, we enable the user to control how compression affects the aesthetic appearance of an image. Adopting a point-based rendering approach to progressive image transmission and compression, we represent an image by a sequence of color values. To best approximate the image at progressive levels of detail, a novel, adaptive farthest point sampling algorithm balances global coverage with local precision. Without storing any spatial information apart from the aspect ratio, the spatial position of each color value is inferred from the preceding members of the sampling sequence. Keeping track of the spatial influence of each sample on the rendition, a progressively generated discrete Voronoi diagram forms the common foundation for our sampling and rendering framework. This framework allows us to extend traditional photorealistic methods of image reconstruction by scattered data interpolation to encompass non-photorealistic rendering. It supports a wide variety of artistic rendering styles based on geometric subdivision or parametric procedural textures. Genetic programming enables the user to create original rendering styles through interactive evolution by aesthetic selection. Comparing our results with JPEG, we conclude with a brief overview of the implications of using non-photorealistic representations for highly compressed imagery
Stylized Rendering for Multiresolution Image Representation
By integrating stylized rendering with an efficient multiresolution image representation, we enable the user to control how compression affects the aesthetic appearance of an image. Adopting a point-based rendering approach to progressive image transmission and compression, we represent an image by a sequence of color values. To best approximate the image at progressive levels of detail, a novel, adaptive farthest point sampling algorithm balances global coverage with local precision. Without storing any spatial information apart from the aspect ratio, the spatial position of each color value is inferred from the preceding members of the sampling sequence. Keeping track of the spatial influence of each sample on the rendition, a progressively generated discrete Voronoi diagram forms the common foundation for our sampling and rendering framework. This framework allows us to extend traditional photorealistic methods of image reconstruction by scattered data interpolation to encompass non-photorealistic rendering. It supports a wide variety of artistic rendering styles based on geometric subdivision or parametric procedural textures. Genetic programming enables the user to create original rendering styles through interactive evolution by aesthetic selection. Comparing our results with JPEG, we conclude with a brief overview of the implications of using non-photorealistic representations for highly compressed imagery
Cross dissolve without cross fade: preserving contrast, color and salience in image compositing
Linear interpolation is the standard image blending method used in image compositing. By averaging in the dynamic range, it reduces contrast and visibly degrades the quality of composite imagery. We demonstrate how to correct linear interpolation to resolve this longstanding problem. To provide visually meaningful, high level control over the compositing process, we introduce three novel image blending operators that are designed to preserve key visual characteristics of their inputs. Our contrast preserving method applies a linear color mapping to recover the contrast lost due to linear interpolation. Our salience preserving method retains the most informative regions of the input images by balancing their relative opacity with their relative saliency. Our color preserving method extends homomorphic image processing by establishing an isomorphism between the image colors and the real numbers, allowing any mathematical operation defined on real numbers to be applied to colors without losing its algebraic properties or mapping colors out of gamut. These approaches to image blending have artistic uses in image editing and video production as well as technical applications such as image morphing and mipmapping. Categories and Subject Descriptors (according to ACM CCS): I.3.3 [Computer Graphics]: Picture/Image Generation 1