The color image has different edge profiles depending on the objects placed in the scene. We propose a novel image-sharpening method adaptive to the local edge slopes with the suppression of background noises. Prescanning the image by a Gaussian derivative (GD) filter, we generate the edge map, which classifies the edge areas to hard, medium, and soft edges, and separates the flat areas without edges. Multiple GD filters with different standard deviations are selectively applied to sharpen each segmented edge area by looking up the edge map. To keep the gray balance, the edge-sharpening filters are applied only to the luminance image. In flat areas except edges, the sharpening filters are resumed and instead, a Gaussian smoothing filter is applied to reduce the background noises. The proposed method brings a dramatic improvement in the reduction of flat-area noises and the natural image-sharpening effects adaptive to the edge slopes. In addition, we newly introduce quality assessment indices to evaluate the image sharpness and flat-area noises with the experimental data.
A 3-D image-to-device gamut mapping algorithm (I-D GMA) is an ideal way to map display image to the inside of printer gamut. A quick decision whether or not each pixel is located inside of the device gamut is necessary to execute a 3-D I-D GMA. We propose a new gamut boundary descriptor (GBD) for comparing the gamut between image and device by the discrete polar angle (,). The gamut shell is described as the simple radial distances, called an r-image. We discuss the location of optimum focal points as mapping centers in an r-image for 3-D I-D GMA. The performance of a 3-D I-D GMA using an r-image is evaluated in the two cases of single and multiple focal points. To maintain the continuous gradation of an image after mapping, the device gamut shell should have a smooth and a precise surface. The printer gamut shell is simply shaped like a polygon made of a triangular mesh pattern, but shaped to have a smoother surface by introducing Overhauser spline functions. Psychophysical experiments were carried out to assess the color appearance matching between the original CRT image and the printed hard copies after mapping. The performance of the 3-D I-D GMA is compared with that of a conventional device-to-device gamut mapping algorithm (D-D GMA). We claim that the 3-D I-D GMA using multiple focal points and a spline GBD achieves the best mapping results for the wide gamut images.
This paper presents an image-dependent color mapping strategy to get the pleasant color renditions from two different approaches: (1) Mapping by Image Segmentation (MAPSEG) (2) Mapping by Histogram Specification (MAPHIST). MAPSEG is basically applied to match the device color to known original. The mappings are performed for the principal component (PC) to be matched in between the segmented areas of original and printed images. MAPHIST works to recover the faded or degraded colors for unknown original. It expands the de-saturated image gamut by Gaussian histogram specification (GHS) and makes full use of device gamut to render the pleasant images.
An object-to-object color mapping strategy depending on the image color contents is proposed. Pictorial color image is segmented into different object areas with clustered color distributions. Euclidian or Mahalanobis color distance measures, and Bayesian decision rule based on maximum likelihood principle, are introduced to the image segmentation. After the image segmentation each segmented pixels are projected onto principal component space by Hotelling transform and the color mapping s are performed for the principal components to be matched in between the individual objects of original and printed images. Experimental results in automatic color correction for inkjet prints are reported. The paper discusses on the color correction effects by PCA matching and reproduction errors in relation to the segmentation methods.
An adaptive color management strategy depending on the image contents is proposed. Pictorial color image is classified into different object areas with clustered color distribution. Euclidian or Mahalanobis color distance measures, and maximum likelihood method based on Bayesian decision rule, are introduced to the classification. After the classification process, each clustered pixels are projected onto principal component space by Hotelling transform and the color corrections are performed for the principal components to be matched each other in between the individual clustered color areas of original and printed images.
We present a novel color processor with programmable
interpolation by small memory (PRISM). The input/output signals to/from the devices are flexibly converted by a 3-0 look-up table (LUT) with a PRISM interpolator. The PRISM architecture provides a simple computation algorithm with sufficient accuracy. The performance of PRISM interpolation is compared with other conventional methods. In practice, PRISM is less complicated than CUBE
and PYRAMID, and more accurate than PYRAMID and
TETRAHEDRON. PRISM cuts the memory size of LUT drastically to an orderof iO compared with a full-size LUT method and brings with it a large-scale integration color processor operating at a higher
than video rate. The PRISM structure is the most suitable for the perceptual color spaces such as YCrCb or CIELAB and very useful for device-independent color reproduction and transmission. Typical applications by a PRISM color processor are presented.
Proc. SPIE. 1244, Image Processing Algorithms and Techniques
KEYWORDS: Detection and tracking algorithms, Image processing, Scanners, Control systems, Printing, Color reproduction, 3D image processing, Evolutionary algorithms, RGB color model, Color and brightness control algorithms
We propose a new algorithm available to variety of real-time color space
transformations : color correction for hardcopy system, perceptual color
control in CIE-LAB space, color coordinate conversions, and color
recognition. This algorithm consists of color look up tables and a new 3D
color space interpolator. This interpolator makes it easy to design a simple
real-time color processor. The simulation shows how the flexible
transformations can be performed without degrading the color and tone.