PPT-Image Filtering – Motion Blur

Ivan Dimitrov 5082012 Photography Fast moving object or a longer exposure time may result in blurring artifacts The same effect can be achieved in a artificial way via image procesing. edusg Chaoqiang Liu Center for Wavelets Approx and Info Proc National University of Singapore Singapore 117542 tslliucqnusedusg Abstract Restoration of a degraded image from motion blurring is highly dependent on the estimation of the blurring kernel Shengyang Dai . and. Ying Wu. EECS Department, Northwestern University. NORTHWESTERN. UNIVERSITY. http. ://vision.middlebury.edu/flow. /. Baker, . Scharstein. , Lewis, Roth, Black, Szeliski, . ICCV’07. Yasmina Schoueri, Milena Scaccia, and . Ioannis. . Rekleitis. School of Computer Science, McGill University. Blur. Movements cause blur in resulting image. Blur regarded as undesirable noise. Related Work. Phong Nguyen & Thuan Pham. CSS 552. Overview. Introduction. Problem Statement. Camera. Importance of Motion Blur. Distributed Rays. Post Processing. Introduction. Camera or eye produce visible streaks from fast moving objects. Kokaram. Co-Supervisor: . Dr.. David . Corrigan. Student: Yun . feng. Wang. Deblurring. in . Atomic Force Microscopy (AFM) . images. Project Description. SFI project: collaboration with . Nanoscale. Steven Lu. Overview. Significance of real-time motion blur rendering (Useful for what?). Slow performance of traditional methods. Some of the modern, more . efficient . methods . have problems, too. A new method is presented . Shengyang Dai . and. Ying Wu. EECS Department, Northwestern University. NORTHWESTERN. UNIVERSITY. http. ://vision.middlebury.edu/flow. /. Baker, . Scharstein. , Lewis, Roth, Black, Szeliski, . ICCV’07. Ivan . Dimitrov. 508/2012. Filtering in . g. eneral . Widespread. Suitable for . Dataflow . Easily upgradable. 2/11. Applying the filter. To apply the filter on the current pixel, you need to use his neighbor pixels. By Percy Mitchell (APSSA,AFIAP). . Panning. . vs. Motion Blur. Panning and motion blur.  These are two techniques that almost every wildlife photographer has played with at some point during their photographic journey.. CS5670: Intro to Computer Vision. Noah Snavely. Hybrid Images, . Oliva. et al., . http://cvcl.mit.edu/hybridimage.htm. Lecture 1: Images and image filtering. Noah Snavely. Hybrid Images, . Oliva. et al., . Fast Filtering Continued. Filtering by . Resampling. This looks like we just zoomed a small image. Can we filter by . downsampling. then . upsampling. ?. Filtering by Resampling. Filtering by Resampling. The next found image lives between what is real and a certain future surrealism. I wonder when I click, Do I manipulate the shot later or leave it as is, crop it or turn it into a photo painting, adding new elements, textures, ideas? On the street, the decisive moment emerges only as a focused blur.. What is an image?. A grid (matrix) of intensity values. . (common to use one byte per value: 0 = black, 255 = white). =. 255. 255. 255. 255. 255. 255. 255. 255. 255. 255. 255. 255. 255. 255. 255. 255. Fouhey. .. Let’s Take An Image. Let’s Fix Things. Slide Credit: D. Lowe. We have noise in our image. Let’s replace each pixel with a . weighted. average of its neighborhood. Weights are . filter kernel.