R.P.C. Janaka Rajapakse

An Automated Color Image Arrangement Method Based on Histogram Matching

We propose a novel color image arrangement method using an elastic transform based on histogram matching on some kinds of axes. The axes include Lightness axis and PC axes obtained from Principal Component Analysis (PCA) in the RGB three-dimensional vector space that is an attribute space of color image. In this paper, we mainly present the principle of its automated color arrangement method especially based on HMGD (Histogram Matching based on Gaussian Distribution). And we describe that the automated method applies the HMGD to input color image only if the image has single-peaked ness in its histogram on the focused axis. In order to detect the single-peaked ness of histogram, the method uses a curvature computation for the cumulative histogram. We show that the method brings about a good sensibility effect (or Kansei effect) in the case of applying the HMGD onto Lightness axis.

Automated color image arrangement method for multiple-peak image

This paper proposes the Histogram Matching based on the Gaussian Distribution (HMGD) method to improve feeling (or Kansei) impression for multiple-peak images. In the previous papers, we have described the HMGD processing. And we also proposed how calculate whether the processing results good or not, using curvature computation. As the results, we have understood that the HMGD processing works well for single-peak images. In this paper, we describe the principle and processing method of HMGD processing to correspond multiple-peak images. And we also illustrate experimental results.

Kansei Impression and Automated Color Image Arrangement Methods (incl. erratum)

This paper proposes a new color image arrangement method using an elastic transform on some kinds of axes. In this paper, we present the principle of our method using HMGD (Histogram Matching based on Gaussian Distribution). And we describe that the automated method applies the HMGD to input color image only when the image has single-peakedness in its histogram on the focused axis. And we describe about HPA-HMGD (Histogram Peakedness Adaptive HMGD) as improvement HMGD. We also show that the method gives a good Kansei effect in the case of applying the HMGD onto Brightness axis. Moreover, we compare processing results of the HPA- HMGD and HMGD, we show that HPA-HMGD is better.

Virtual Reconstruction and Visualization of Pre and Proto Historic Landscapes in Srilanka

3D Computer graphics and advanced media technologies have long been used to preserve or virtually visualize cultural heritage sites. While a number of research work on preservation and virtual reconstructions of archeological sites in Europe and Egypt, less effort has been spent on introducing new technologies to visualize and preserve cultural heritage sites in some other regions of the world like south Asia. This research presents a case study focused on the virtual visualization and simulation of pre and proto historic landscapes in Sri Lanka. The transition between prehistory and protohistory of Sri Lanka is not precisely clear, that would have occurred in the mid or late Holocene. Recently, archeological researchers have focused on the proto historic culture of the Uda Walave River Basin in Sri Lanka. This area has identified as an environmentally optimal area apt to probe the question of pre and proto historic transition in Sri Lanka. The main goal of this paper is to visualize and virtually reconstruct pre and proto historic culture in the Uda Walave River Basin; based on recent archeological data and findings.

Regression Analysis Based Variance Estimation of Gaussian Distribution for Histogram Matching

This paper describes an improved method of the variance estimation of Gaussian distribution for Histogram Matching based on Gaussian Distribution (HMGD). In our previous paper, focusing on the symmetry of the Gaussian function, we presented another method for the variance (or Gaussian width) estimation of Gaussian distribution in the original histogram. However, since the real shape of mountain like Gaussian function in the original image’s histogram does not always show the good symmetry, the variance estimation method that we previously presented did not work so well as we expected. In this paper, we newly propose the improved estimation method using regression analysis, based on curvature computation for the cumulative histogram of original image’s one. In the newly proposed method, first, we detect the histogram peak of original image’s histogram by using curvature computation; next, we perform the regression analysis for the cumulative histogram, using an approximated function of the curvature that includes the variance parameter. Also in this paper, we show some experimental results by the estimation method.

Automated Processing of Multiple-Brightness Peak Histogram Image Using Curvature and Variance Estimation

Previously, we have illustrated that the Histogram Matching based on Gaussian Distribution (HMGD) is an effective automated image processing method for obtaining a better feeling impression image. However, the simple HMGD works only for the image whose histogram has just one peak. For the image whose histogram has multiplebrightness peak, it does not work as in the case of single peak histogram image. In this paper, we propose the improved method for multiple-brightness peak (HMGD-MBP). This method can not only detect multiple peaks but also estimate the variance of Gaussian distribution at each detected peak in the image histogram, using curvature computation. This paper also presents the effectiveness of the proposed method by showing the experimental results.

Real-time rendering of colour-shift effect of metallic materials

The directional-dependent effects of the materials are responsible for our perception of certain materials being realistic or not. Some materials consist of colour pigments, and these cause directional-dependent colour variations (or colour-shifts). For instance, we can observe a colour-shift effect of metallic materials, which means the changing of colour from metallic colour to pigment colour depending on the direction of incident illumination and direction of view. The most common criticism of existing analytical Bidirectional Reflectance Distribution Function (BRDF) models is that these models are inadequate to generate colour-shift effect of materials for realistic real-time rendering. This paper introduces a visually plausible shading model to generate colour-shift effect of metallic materials by modifying specular component with illumination and view dependent sheen. The developed shaders have intuitive parameters, which can generate different kinds of metallic effects for real-time rendering, including visually plausible gold, brass, silver, bronze and copper effects for real-time rendering.