Masato Toda

High dynamic range rendering for YUV images with a constraint on perceptual chroma preservation

A new high dynamic range rendering (HDRR) suitable for YUV images is presented. The method overcomes the problem on saturation decrease caused by the conventional HDRRs for YUV images. U and V components are corrected with an approximating function that is designed to preserve the metric chroma in CIELAB before and after an HDRR. The function is derived from the relationship between the changes in the Y component and those in the chroma. The color differences between the images corrected by our method and the ideal images were found to be in an acceptable range, where they can be recognized as being the same color. Our method achieved the highest score in a subjective assessment of preserving the perceptual chroma when it was compared with other methods.

High dynamic range rendering method for YUV images with global luminance correction

This paper proposes a high dynamic range rendering method which consists of local luminance correction and global luminance correction. The proposed method estimates the change in the global luminance caused by the local luminance correction in advance, and sets an approximate gamma value for each pixel. The local luminance correction and the global luminance correction are combined to reduce the computation cost in the method. Experiments results demonstrated that the proposed method can successfully enhance image quality and its computational cost is reasonable for imaging appliances.

Efficient implementation of Filtering-Direction-Controlled Digital TV Filter for image denoising

We propose the efficient implementation of Filtering-Direction-Controlled Digital Total-Variation Filter (FDC-DTVF) for real-time image denoising. FDC-DTVF produces a clear image compared to the conventional pixel-based denoising methods, but has not yet to be considered regarding its efficient implementation. We conduct algorithm optimization by reusing a calculated criterion that is newly introduced in FDC-DTVF, since the criterion is almost invariant in each step of the iterative process. We also conducted a software implementation so we can more efficiently use the CPU resource. The simulation results showed that our implementation achieves the real-time processing for a VGA video, while maintaining the image denoising performance.

Image quality enhancement method based on scene category classification and its evaluation

This paper presents a method of enhancing image quality based on the analysis of scene categories, and its practical software implementation. The proposed method analyzes the scene of input images and calculates the probabilities for five predetermined scene categories; i.e. “Portraits,” “Landscapes,” “Night scenes,” “Flowers (close-up)” and “Others.” The quality of the input image is improved by using multiple image-processing functions with correction parameters, which take the probabilities of the scene categories into consideration. Subjective experiments on image quality show the reliability of the proposed method.

Foreground Detection Robust Against Cast Shadows in Outdoor Daytime Environment

This paper proposes a novel foreground detection method which estimates the color changes in shadow regions by using a solar spectral model. In conventional method, since it is assumed that only brightness changes from background in shadow regions, shadow regions are extracted falsely as foreground in the case where color in the shadow region also changes in outdoor daytime environment. The proposed method estimates the color changes in shadow regions by calculating colors of direct and ambient illuminance which radiate to the captured scene using a solar spectral model. By estimating the color changes, the proposed method can robustly distinguish foreground and shadow regions in outdoor daytime environment. Experimental results demonstrate that the proposed method successfully estimates the changes of background color in shadow regions and improves F-measure of foreground detection compared with the conventional methods.

Image Clarification Method Based on Structure-Texture Decomposition with Texture Refinement

This paper presents a high quality and low complexity image clarification method, which restores the visibility of images captured in bad weather and poor lighting conditions. A sequential processing of conventional dehazing and backlit correction methods has a problem that textures and noises are overemphasized by the corrections. The proposed method first decomposes a captured image into two components: a structure component forming smooth regions and strong edges and a rest component for fine textures and noises. Image enhancement is conducted based on analyses of the first component, while controlling an amplification factor of the texture component. The utilization of the structure component for the enhancement enables pixel-wise corrections without local area analysis which results in lower computational cost. Experimental results demonstrate that the proposed method can successfully enhance image qualities and its computational cost is reasonable for real-time video processing.

A Novel Method for Simultaneous Acquisition of Visible and Near-Infrared Light Using a Coded Infrared-Cut Filter

This paper presents a novel image sensing method to enhance the sensitivity of a camera. Most image sensors used in commercial digital cameras are sensitive for both visible and infrared light. An IR-cut filter, that obstructs the infrared component of natural light, is used in such cameras to realize a similar color reproduction as for the human visual system. However, recent studies have shown that the near infrared light contains useful information to further enhance the visible image. This paper introduces a new sensing method by using a coded IR-cut filter to enable simultaneous capturing of NIR and visible light on a single image sensor. The coded IR-cut filter lets a fraction of the near infrared light pass and blocks out the rest. Both visible and near infrared light images can be separated from the sensor output when taking the diffraction of the NIR light into account. Experiments, using a synthesized image sensor output, demonstrate the validity of the method.