In physical implementation, the quality of net open location finder would directly impact the quality of final routing result. It is important to consider both of the length of indicated paths and the turnaround time. To address this problem, the ICCAD-2017 contest encourages the research in obstacle-aware multi-layer shortest paths finding and the corresponding speedup techniques. We provided (i) a set of benchmarks and (ii) an evaluation metric that facilitate contestants to develop and test their new algorithms.

In this paper, we investigate the assessment of image realism by focusing our attention on the color compatibility between an inserted object and the background in an image composite. We propose a technique based on two color compatibility properties to achieve realistic image composition. The first property is related to the color similarity, and the second one to the consistence of color tendency between image regions. We further propose algorithms based on these two properties for image realism assessment and recoloring. These algorithms only require information from the image to be tested, making them suitable for practical applications where real images are unavailable. Effectiveness of the algorithms is demonstrated through various images and verified by ground truth.

In this paper, we present a study of the realism of color image composites. Assessing the realism of image composites has emerged as a new field of image processing due to the advances in digital imaging and communications. However, when making image composites, users often suffer from color incompatibility between the inserted object and the background. We observe two properties that help make an image composite look realistic. The first property is related to the color similarity between different segments of the image, and the second one is related to the consistency of color deviation between the segments. These two properties only require information available from a single image. An algorithm based on these two properties is proposed for assessment of image realism. Effectiveness of the algorithm is demonstrated.

In this paper, we present a system including a novel component called programmable aperture and two associated post-processing algorithms for high-quality light field acquisition. The shape of the programmable aperture can be adjusted and used to capture light field at full sensor resolution through multiple exposures without any additional optics and without moving the camera. High acquisition efficiency is achieved by employing an optimal multiplexing scheme, and quality data is obtained by using the two post-processing algorithms designed for self calibration of photometric distortion and for multi-view depth estimation. View-dependent depth maps thus generated help boost the angular resolution of light field. Various post-exposure photographic effects are given to demonstrate the effectiveness of the system and the quality of the captured light field.