PPT-Pixels and Image Filtering

Computational Photography Derek Hoiem 083117 Graphic httpwwwnotcotorgpost4068 Administrative stuff Any questions Tutorial Looks like Sept 6 at 5pm lasting 152 hrs . Capturing and Editing Digital Images. 1. Scanners. Types. Flatbed. Sheet-fed. Handheld. Drum. Resolution. Optical resolution. Enhanced resolution. Reported in dpi (dots per inch). 2. How Scanners Work. Spectr. . scopy. with NIRISS. Van Dixon. STScI. JWST FGS. TIPS/JIM. 2012 September 20. . NIRISS at a Glance. Parameter. Value. Array Size. 2048 x 2048 (2040 x 2040 active). Pixel size. 18 . μm. x 18 . Graph Cuts. Seam Carving. Video. Make images smaller by removing “seams”. Seam = connected path of pixels . from top to bottom. or left edge to right edge. Don’t want to remove important stuff. Lecture 20: Image Enhancement in Frequency Domain. Recap of Lecture 19. Spatial filtering. Mean Filter. Non-Local Mean Filter. Median Filter. Unsharp. Masking. Adaptive . Unsharp. Masking. Outline of Lecture 20. Lecture 5. : Pixels Relationships. Recap of Lecture 4. Different pixel relationships. Neighbourhood. Connectivity. Adjacency. Path. Connected component labelling. Outline. Different distance measures. By. Dr. Rajeev Srivastava. What is Morphology?. Definition. The filters can be described using set theoretic notation . A set is a collection of pixels in the context of an image.. Morphological Operations. Segmentation . algorithms. By. Dr.. Rajeev . Srivastava. Contents. Introduction. Image segmentation algorithms. Evaluation Metrics. Result for segmentation. Introduction. Segmentation subdivides the image into its constituents region or objects.. r. s. t. u. v. w. x. y. z. Origin. x. y. Image f (x, y). e. processed. = . v. *e + . . r. *a + . s. *b + . t. *c + . . u. *d + . w. *f + . . x. *g + . y. *h + . z. *. i. Filter. Simple 3*3. Neighbourhood. Computer Vision. Filtering and Edge Detection. Connelly Barnes. Slides from Jason Lawrence, . Fei. . Fei. Li, Juan Carlos . Niebles. , Misha . Kazhdan. , Allison Klein, Tom . Funkhouser. , Adam Finkelstein, David . 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. Photoshop & Photos (Cont.). Overview. Working with the Move Tool. Using the Crop Tool. Cloning Parts of an Image with the Clone Tool. Image Resizing & Prepping for Use. The Move Tool. Has two primary uses:. 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.