Accurate assessment of the quality of concrete bridge decks and identification of corrosion induced delamination lead to economic management of bridge decks. It has been demonstrated that ground penetrating radar (GPR) can be successfully used for such purposes. The growing demand on GPR has brought into the challenge of developing automatic processes necessary to produce a final accurate interpretation. However, there have been few publications targeting at automatic detection of bridge deck delamination from GPR data. This paper proposes a novel method using partial differential equations to detect rebar (or steel-bar) mat signatures of concrete bridges from GPR data so that the delamination within the bridge deck can be effectively located. The proposed algorithm was tested on both synthetic and real GPR images and the experimental results have demonstrated its accuracy and reliability, even for diminished image contrast and low signal-to-noise ratio. Therefore, an accurate deterioration map of the bridge deck can be generated automatically.

Despite considerable progress in HDR image tone mapping for the past decade, little work has been done for HDR video. For applications such as film post-production, the capability of local tone manipulation is highly regarded by the content creators. This paper presents an interactive tone mapping scheme for HDR video sequences. It provides a simple scribble/stroke based interface for local tone manipulation and is capable of propagating user input information throughout a video sequence by using Gaussian mixture model (GMM) and edge preserving filtering. The experimental results demonstrated its effectiveness for HDR video tone mapping as well as its flexibility for users to easily and intuitively manipulate the appearance of the video while maintaining temporal consistency.

In recent years, non-uniform LED based backlighting techniques have been used to build display prototypes and products with extremely high dynamic range, thus making possible to show video content with very high fidelity. These displays have two modulation channels: a low resolution LED layer that provides non-uniform backlighting, and a high resolution LCD front panel for color. Unfortunately, displaying an HDR image on such screens is not straightforward because the lower resolution of the LED layer and the cross-talk between LEDs make not possible to individually control the output of each pixel. Using the wrong backlighting results in low image quality and may even lead to visual artifacts such as false contouring and visible LED patterns. In this paper, we characterize the LED/LCD display using a general model and formulate the backlighting computation as an optimization problem. We further propose an iterative algorithm to solve the optimization problem. Compared to existing methods, our model is more precise and provides better image quality on the same display device.

A method is proposed for reducing the visibility of "contour artifacts," i.e., false contours resulting from color quantization in digital images. The method performs a multiscale analysis on the neighborhood of each pixel, determines the presence and scale of contour artifacts, and probabilistically dithers (perturbs) the color of the pixel. The overall effect is to "break down" the false contours, making them less visible. The proposed method may be used to reduce contour artifacts at the same bit depth as the input image or at higher bit depths. The contour artifact detection mechanism ensures that artifact-free regions remain unaffected during the process.

A method is proposed for reducing the visibility of "banding artifacts," i.e. false contours resulting from color quantization in digital images. The method performs a multi-scale analysis on the neighborhood of each pixel, determines the presence and scale of banding artifacts, and probabilistically dithers (perturbs) the color of the pixel. The overall effect is to "break down" the false contours making them less visible. The proposed method may be used to reduce banding artifacts at the same bit depth as the input image or at higher bit depths. The banding detection mechanism ensures that artifact-free regions remain unaffected during the process.

The masking property of human vision systems has been successfully applied in various image/video applications. To invoke the spatial masking effect, it is important to design a metric that effectively identifies the spatial activity of a region. This metric indicates which areas are more textured and more artifacts can be masked. We review three widely used metrics and evaluate their performance in context of film content. We observe that these metrics have strong dependencies on the brightness. More specifically, for smooth areas with film grain, these metrics usually assign greater degrees of texture to the bright regions and lower degrees to dark ones. This causes problems in the bright areas that are mistakenly identified as more textured than the dark areas. Utilizing the property of film grain, we explain the origin of this dependency and propose a new spatial activity metric that removes the dependency on the brightness. In our simulation, we use this new metric in the rate control algorithm of a MPEG-2 video encoder. The result shows more homogeneous film grain in the reconstructed pictures and improved visual quality.