Flash Photography Enhancement via Intrinsic Relighting

We enhance photographs shot in dark environments by combining a picture taken with the available light and one taken with the flash. We preserve the ambiance of the original lighting and insert the sharpness from the flash image. We use the bilateral filter to decompose the images into detail and large scale. We reconstruct the image using the large scale of the available lighting and the detail of the flash. We detect and correct flash shadows. This combines the advantages of available illumination and flash photography.Singapore-MIT Alliance (SMA

Learning to Hallucinate Face Images via Component Generation and Enhancement

We propose a two-stage method for face hallucination. First, we generate facial components of the input image using CNNs. These components represent the basic facial structures. Second, we synthesize fine-grained facial structures from high resolution training images. The details of these structures are transferred into facial components for enhancement. Therefore, we generate facial components to approximate ground truth global appearance in the first stage and enhance them through recovering details in the second stage. The experiments demonstrate that our method performs favorably against state-of-the-art methodsComment: IJCAI 2017. Project page: http://www.cs.cityu.edu.hk/~yibisong/ijcai17_sr/index.htm

Stylizing Face Images via Multiple Exemplars

We address the problem of transferring the style of a headshot photo to face images. Existing methods using a single exemplar lead to inaccurate results when the exemplar does not contain sufficient stylized facial components for a given photo. In this work, we propose an algorithm to stylize face images using multiple exemplars containing different subjects in the same style. Patch correspondences between an input photo and multiple exemplars are established using a Markov Random Field (MRF), which enables accurate local energy transfer via Laplacian stacks. As image patches from multiple exemplars are used, the boundaries of facial components on the target image are inevitably inconsistent. The artifacts are removed by a post-processing step using an edge-preserving filter. Experimental results show that the proposed algorithm consistently produces visually pleasing results.Comment: In CVIU 2017. Project Page: http://www.cs.cityu.edu.hk/~yibisong/cviu17/index.htm

Использование билатерального фильтра для оценки и анализа отклонений геометрии поверхностей

В работе проведены измерения координат точек плоской поверхности, обработанной шлифованием, на координатно-измерительной машине. В измеренных точках рассчитаны отклонения от номинальной геометрии и проведены серии экспериментов по фильтрации значений отклонений от погрешности средства измерения. Проведен анализ соответствия отфильтрованной погрешности нормальному закону распределения. Так же проведен корреляционный анализ. Рассмотренный в работе фильтр и анализ результатов его применения реализованы в программном пакете MATLAB и могут быть применены в программном обеспечении измерительных средств при контроле отклонений геометрии различных деталей

Bright Lesion Detection in Color Fundus Images Based on Texture Features

In this paper a computer aided screening system for the detection of bright lesions or exudates using color fundus images is proposed. The proposed screening system is used to identify the suspicious regions for bright lesions. A texture feature extraction method is also demonstrated to describe the characteristics of region of interest. In final stage the normal and abnormal images are classified using Support vector machine classifier. Our proposed system obtained the effective detection performance compared to some of the state–of–art methods