11/29/2015 1 Image Processing. 11/29/2015 2 Systems and Software Image file formats Image processing applications.

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Presentation transcript:

11/29/ Image Processing

11/29/ Systems and Software Image file formats Image processing applications

11/29/ Image file formats Pixel images Graphic images Composite image files Images in manuscripts Graphic

11/29/ Format issues Color, monochrome Capability –Gray value –Graphics –Calibration: size, sensitometry, etc... Compatibility Compression

11/29/ Common formats TIFF –Common usage –Versatile: pixel, calibration –Pixel-based regions –Dialects Raw EPS –versatile –primarily, printed document format PICT, PICS –well developed standard –pixel and graphic format –primarily Macintosh

11/29/ Common formats (more) DICOM –used in medical imaging Graphic arts: –MPEG, JPEG, GIF Import menu in NIH Image

11/29/ Image processing software functions Image acquisition Image processing Quantitative data extraction Annotation and editing Database management File format conversion

11/29/ Image processing software structure Task-dedicated General purpose Scripting/macro language

11/29/ Software package examples NIH Image – Adobe Photoshop

11/29/ Examples NIH Image & file conversion Annotation Copying, pasting

11/29/ Software selection issues Compatibility with computer Functionality –Control of acquisition hardware (compatibility) –Range of processing algorithms Productivity

11/29/ Image processing Contrast manipulation and enhancement Dyadic operation Image filtering Regions and region operation Image analysis

11/29/ Monadic (one picture) operations Contrast manipulation and enhancement LUT operation –brightness, contrast –False color Gray value remap (apply LUT) Arithmetic operations Scale and rotate (also morphing) Other single image operations

11/29/ Monadic operations Profile plot (and projection) Gray value histogram

11/29/ Display operations Gray scale manipulation False color manipulation Enlarge, contract, scale to fit window See Adobe Illustrator for image editing

11/29/ Example of rotation (a)(b)(c) (a) Original image, (b) rotated by 1.2°, nearest neighbor interpolation, (c) rotated by 1.2 °, bilinear interpolation.

11/29/ Examples of histograms

11/29/ Dyadic (two image) operations Dyadic (two variable) function: Examples: addition, multiplication, subtraction, and division. Problem: finite numerical range fro picture gray value leads to roundoff.

11/29/ Example: shading correction

11/29/ Image Filtering Convolution Rank filtering Edge detection

11/29/ Image filtering (conceptual)

11/29/ Convolution with the Fourier transform

11/29/ Examples of linear filters Low-pass (smooth, Gauss) High-pass (sharpen, Mexican Hat, DOG) Shadow First derivative (shadow, find edges)

11/29/ Example of smoothing Smoothing (5 times) BeforeAfter

11/29/ Convolve Original Gauss (7x7) ‘Mexican hat’(17x17) Grad N Grad W

11/29/ Nonlinear filters Median (noise eliminate and enhance) Minimum (erode) Maximum (dilate) Open Close

11/29/ Example of morphological (rank) filters Opening (3) Closing (3) Original Minimum, erode (1) Maximum, dilate (1)

11/29/ Example, grain counting Grain imageMaximum (5) Difference

11/29/ Regions and region operation Thresholding, density slicing Erosion, dilation (rank filtering) Skeletons

11/29/ Image analysis Sensitometric Geometric Categorical (image recognition)

11/29/ Segmentation Geometrical shapes Interactive (outlining) Thresholding Filling

11/29/ Segmentation - connected area Density slice, then use wand (auto-outline) to trace outline. Outline written on image with ‘draw boundary’ command.

11/29/ Region of interest (ROI) analysis Area Perimeter Shape Average value Standard deviation

11/29/ Example of measurement AreaMeanLengthMinorMajor

11/29/ Summary Paradigm: scanning, preprocessing, analysis Success depends on all parts of analysis chain Quality control –Quantitative evaluation of performance –Test samples –Repeated analysis

11/29/ Summary Digital image acquisition - physical data to numbers Control of accuracy Experimental design Experimental preparation Scanner Scanner in the lab Complex device, operation and maintenance Quality control mandatory

11/29/ Houston, we have a problem.