IEEE International Conference on Computational Photography (ICCP)最新文献_第2页

What does an aberrated photo tell us about the lens and the scene? 一张像差照片告诉我们关于镜头和场景的什么信息?

IEEE International Conference on Computational Photography (ICCP) Pub Date : 2013-04-19 DOI: 10.1109/ICCPhot.2013.6528316

Huixuan Tang, Kiriakos N. Kutulakos

引用次数: 25

Descattering of transmissive observation using Parallel High-Frequency Illumination 平行高频照明透射观测的散射

IEEE International Conference on Computational Photography (ICCP) Pub Date : 2013-04-19 DOI: 10.1109/ICCPhot.2013.6528300

Kenichiro Tanaka, Y. Mukaigawa, Y. Matsushita, Y. Yagi

引用次数: 23

A generative focus measure with application to omnifocus imaging 一种用于全焦成像的生成式焦距测量方法

IEEE International Conference on Computational Photography (ICCP) Pub Date : 2013-04-19 DOI: 10.1109/ICCPhot.2013.6528295

Avinash Kumar, N. Ahuja

{"title":"A generative focus measure with application to omnifocus imaging","authors":"Avinash Kumar, N. Ahuja","doi":"10.1109/ICCPhot.2013.6528295","DOIUrl":"https://doi.org/10.1109/ICCPhot.2013.6528295","url":null,"abstract":"Given a stack of registered images acquired using a range of focus settings (focal stack images), we propose a new focus measure to identify the most focused image. Although, most of the paper is concerned with the new focus measure, for evaluation purposes, we will present it in the context of an application to generating omnifocus images. An omnifocus image is the composite image in which each pixel is selected form the frame in the stack in which it appears to be in best focus. Conventional focus measures usually maximize some measure of image gradient in a window. They tend to fail when one of the edges of the window lies near the boundary of an intensity edge, or the pixel is near other complex edge patterns. This leads to the misidentification of the focused frame and formation of artifacts in omnifocused image. Our proposed measure does not attempt to identify the focused frame by calculating the degree of defocus, like the gradient based methods. Rather, it hypothesizes that a specific frame is in focus and then validates or rejects this hypothesis by recreating the defocused frames in the vicinity, and comparing them with the observed de-focused frames. This forward generative process leads to correct focus frame selection in regions where typical measures fail. This is because the conventional measures try to identify the focused frame from its distorted version which is the result of a complex convolution process. This involves a backward estimation for a many-to-one transformation. On the other hand, the generation of defocused frames from a hypothesized focused frame is more accurate since it involves applying an operator in the forward direction. We analytically show that under ideal imaging conditions, the proposed focus measure is unimodal in nature. This makes the search for the best focused image unambiguous. We evaluate our focus measure by generating omnifocus images from real focal stack images, and show that it performs better than all the existing focus measures.","PeriodicalId":289563,"journal":{"name":"IEEE International Conference on Computational Photography (ICCP)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123303220","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 12

Outdoor photometric stereo 室外光度立体

IEEE International Conference on Computational Photography (ICCP) Pub Date : 2013-04-19 DOI: 10.1109/ICCPHOT.2013.6528306

L. Yu, Sai-Kit Yeung, Yu-Wing Tai, Demetri Terzopoulos, T. Chan

引用次数: 30

Focal sweep videography with deformable optics 焦扫描摄像与变形光学

IEEE International Conference on Computational Photography (ICCP) Pub Date : 2013-04-19 DOI: 10.1109/ICCPhot.2013.6528302

Daniel Miau, O. Cossairt, S. Nayar

引用次数: 25

Transformation guided image completion 变换引导图像补全

IEEE International Conference on Computational Photography (ICCP) Pub Date : 2013-04-19 DOI: 10.1109/ICCPhot.2013.6528313

Jia-Bin Huang, J. Kopf, N. Ahuja, S. B. Kang

引用次数: 30

Unified HDR reconstruction from raw CFA data 从原始CFA数据统一HDR重建

IEEE International Conference on Computational Photography (ICCP) Pub Date : 2013-04-19 DOI: 10.1109/ICCPhot.2013.6528315

J. Kronander, S. Gustavson, G. Bonnet, J. Unger

引用次数: 74

The omnipolar camera: A new approach to stereo immersive capture 全极相机:立体沉浸式捕捉的新方法

IEEE International Conference on Computational Photography (ICCP) Pub Date : 2013-04-19 DOI: 10.1109/ICCPhot.2013.6528311

V. Chapdelaine-Couture, S. Roy

引用次数: 16

Combining the power of Internal and External denoising 结合内部和外部去噪的力量

IEEE International Conference on Computational Photography (ICCP) Pub Date : 2013-04-19 DOI: 10.1109/ICCPhot.2013.6528298

Inbar Mosseri, Maria Zontak, M. Irani

{"title":"Combining the power of Internal and External denoising","authors":"Inbar Mosseri, Maria Zontak, M. Irani","doi":"10.1109/ICCPhot.2013.6528298","DOIUrl":"https://doi.org/10.1109/ICCPhot.2013.6528298","url":null,"abstract":"Image denoising methods can broadly be classified into two types: “Internal Denoising” (denoising an image patch using other noisy patches within the noisy image), and “External Denoising” (denoising a patch using external clean natural image patches). Any such method, whether Internal or External, is typically applied to all image patches. In this paper we show that different image patches inherently have different preferences for Internal or External de-noising. Moreover, and surprisingly, the higher the noise in the image, the stronger the preference for Internal De-noising. We identify and explain the source of this behavior, and show that Internal/External preference of a patch is directly related to its individual Signal-to-Noise-Ratio (“PatchSNR”). Patches with high PatchSNR (e.g., patches on strong edges) benefit much from External Denoising, whereas patches with low PatchSNR (e.g., patches in noisy uniform regions) benefit much more from Internal Denoising. Combining the power of Internal or External denoising selectively for each patch based on its estimated PatchSNR leads to improvement in denoising performance.","PeriodicalId":289563,"journal":{"name":"IEEE International Conference on Computational Photography (ICCP)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132771916","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 103

Simultaneous HDR image reconstruction and denoising for dynamic scenes 动态场景的同步HDR图像重建和去噪

IEEE International Conference on Computational Photography (ICCP) Pub Date : 2013-04-19 DOI: 10.1109/ICCPhot.2013.6528309

C. Aguerrebere, J. Delon, Y. Gousseau, P. Musé

{"title":"Simultaneous HDR image reconstruction and denoising for dynamic scenes","authors":"C. Aguerrebere, J. Delon, Y. Gousseau, P. Musé","doi":"10.1109/ICCPhot.2013.6528309","DOIUrl":"https://doi.org/10.1109/ICCPhot.2013.6528309","url":null,"abstract":"High dynamic range (HDR) images are usually generated by combining multiple photographs acquired with different exposure times. This approach, while effective, suffers from various drawbacks. The irradiance estimation is performed by combining, for each pixel, different exposure values at the same spatial position. This estimation scheme does not take advantage of the redundancy present in most images. Moreover, images must be perfectly aligned and objects must be in the exact same position in all frames in order to combine the different exposures. In this work, we propose a new HDR image generation approach that simultaneously copes with these problems and exploits image redundancy to produce a denoised result. A reference image is chosen and a patch-based approach is used to find similar pixels that are then combined for the irradiance estimation. This patch-based approach permits to obtain a denoised result and is robust to image misalignments and object motions. Results show significant improvements in terms of noise reduction over previous HDR image generation techniques, while being robust to motion and changes between the exposures.","PeriodicalId":289563,"journal":{"name":"IEEE International Conference on Computational Photography (ICCP)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126939471","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 19