Introduction to Image Processing Introduction to Image Processing Presented by: Nicholas Beavers – Media Cybernetics, Inc. Welcome to Sponsored by Starting Soon…

Introduction to Imaging Processing presented by Media Cybernetics © What is an image? An image is a numerical representation of a “picture.” – a set of numbers interpreted by the computer which creates a visual representation that is understood by humans

Introduction to Imaging Processing presented by Media Cybernetics © Pixels are identified by their position in a grid (two-dimensional array), referenced by its row (x), and column (y). Image: Pixel Array Pixel = Picture Element Each pixel is a sample of an original image.

Introduction to Imaging Processing presented by Media Cybernetics © Binary Digits (bits) Bitonal 0 = Black 1 = White

Introduction to Imaging Processing presented by Media Cybernetics © BIT DEPTH is determined by the number of bits used to define each pixel. The greater the bit depth, the greater the number of tones (grayscale or color) that can be represented. What is bit-depth?

Introduction to Imaging Processing presented by Media Cybernetics © BitsTonesBinary DigitsArray 1 bit (2 1 )2 tones (0 – 1) 0 or 1 2 bits (2 2 )4 tones (0 – 3) 00, 01, 10, 11 3 bits (2 3 )8 tones (0 – 7) 000, 001, 010, 011, 100, 101, 110, bits (2 4 )16 tones (0 – 15) 0000, 0001, 0010, 0100, 1000, 0011, 0101, 1001, 1010, 0111, 1011, 1100, 1101, 1110, 1111, 0110

Introduction to Imaging Processing presented by Media Cybernetics © BitsTonesBinary DigitsArray 8 bit (2 8 )256 tones (0 – 255) , , etc. 12 bits (2 12 )4,096 tones (0 – 4,095) , , etc. 16 bits (2 16 )65,536 tones (0 – 65,535) , , etc. 24 bits (2 24 )16.7 million tones (0 – 16,699,999) , , etc.

Introduction to Imaging Processing presented by Media Cybernetics © The number of pixels in the image must be sufficient to distinguish features of interest: Resolution

Introduction to Imaging Processing presented by Media Cybernetics © Aliasing: Distortion introduced when an image of high resolution is sampled by a detector of lower resolution. Resolution

Introduction to Imaging Processing presented by Media Cybernetics © 1x  m/pixel 2x  m/pixel 3x  m/pixel 4x  m/pixel Same display settings Different contrast and brightness Images courtesy of Claire M. Brown, PhD, McGill University Department of Biochemistry Binning

Introduction to Imaging Processing presented by Media Cybernetics © Zoom  m/pixel Zoom  m/pixel Zoom  m/pixel Zoom  m/pixel Zoom  m/pixel 63X NA 1.4 Oil Images courtesy of Claire M. Brown, PhD, McGill University Department of Biochemistry Over Sampling

Introduction to Imaging Processing presented by Media Cybernetics © Input device – the source of the images; camera, microscope, scanner, etc Interface hardware – the connection between the input device and the computer; takes the input signal and digitizes it for use on a PC Imaging software – the user interface to all the imaging components Output devices – printers, image storage devices, monitors What components are involved in imaging?

Introduction to Imaging Processing presented by Media Cybernetics © Capture only or “driver” software: software used to capture and save an image from a device – developed mostly by hardware manufacturers Example: TWAIN drivers “Imaging” software, Image Editing, Photo Retouching: software used primarily in home and general business applications, mostly consumer oriented Example: Adobe PhotoShop, Microsoft Photo Editor, Image Tools Basic Image Measurement Software: used for basic image capture, enhancement, with simple measuring tools Example: Image-Pro Express Types of Imaging Software

Introduction to Imaging Processing presented by Media Cybernetics © General Analytical Image Analysis Software: used in scientific/industrial analysis of images to generate proven data Example: Image-Pro Plus Vertical Market Image Analysis Software: used to solve specific imaging problems in a related industry Example: Array-Pro, Scope-Pro, Materials-Pro Analyzer, or vision software libraries Types of Imaging Software cont…

Introduction to Imaging Processing presented by Media Cybernetics © Sample Preparation* Acquisition – how do we acquire an image into the computer? Enhancement – how do we make it look better to extract information? Identification – which attributes of the image are we interested in? Measurement – what information can we obtain? Report Generation – how can we present this information? Archive – how can we store the information? The Analytical Imaging Process

Introduction to Imaging Processing presented by Media Cybernetics © There are basic ways to enhance an image: Modify its intensity index: brightness, contrast, gamma Background correction: flatten, compensate for irregularities Apply a spatial filter or operation: sharpen, low-pass, edge Advanced enhancement Manipulate the image frequencies: Fourier transform Morphological transformations: erode, dilate, both… Image Enhancement

Introduction to Imaging Processing presented by Media Cybernetics © Black: 0 White: 255 for 8-bit images : 4095 for 12-bit images The higher the bit depth, the better the dynamic range of the image – allowing for greater information observance in “sensitive” samples Image Enhancement: Brightness Overall amount of “light” in an image (2 n –1) for n-bit images

Introduction to Imaging Processing presented by Media Cybernetics © Low dynamic range Medium contrast Full dynamic range Good contrast Enhancement: Grey-value Histogram Stretch

Introduction to Imaging Processing presented by Media Cybernetics © brightness contrastAll Three lineargamma 0.5gamma 2 Image Intensity Display Intensity Images courtesy of Claire M. Brown, PhD, McGill University Department of Biochemistry Image Enhancement: All Three

Introduction to Imaging Processing presented by Media Cybernetics © BackgroundAutomatic flatten of Background Original Image Enhancement: Background Correction

Introduction to Imaging Processing presented by Media Cybernetics © Commonly used convolution filters: Low-pass: blurs, or smoothes an object Sharpen: enhances all intensity transitions Hi-pass: creates harsh intensity variations Median: removes random impulse noise Advanced Filters: Sigma: removes local impulse noise without Image Enhancement: Spatial Filtering

Introduction to Imaging Processing presented by Media Cybernetics © Examples of filter kernels: horizontalvertical sharpening edge detectedge detectfilter Spatial Filters

Introduction to Imaging Processing presented by Media Cybernetics © Kernel size Preview window Filter description Sharpen Filter

Introduction to Imaging Processing presented by Media Cybernetics © Examples Image Enhancement: Sharpening

Introduction to Imaging Processing presented by Media Cybernetics © Utilizing the Image-Pro Plus © software package. Live Image Processing

Introduction to Imaging Processing presented by Media Cybernetics © Provides a method for combining two or more images into a single resultant image. The final results will depend on the operation performed. Logical: AND OR NOT NAND XOR Arithmetic: Add Average Subtract Difference Max & Min Arithmetic operators

Introduction to Imaging Processing presented by Media Cybernetics © DAPI Cy3 FITC Processing / Enhancement Merge Images

Introduction to Imaging Processing presented by Media Cybernetics © Red Green Blue Processing / Enhancement Extract Images

Introduction to Imaging Processing presented by Media Cybernetics © Extended Depth of Field

Introduction to Imaging Processing presented by Media Cybernetics © Depth of Field Extended Depth of Field cont…

Introduction to Imaging Processing presented by Media Cybernetics © “Stitching” of Images through Automatic Microscope and Stage control Tiling

Introduction to Imaging Processing presented by Media Cybernetics © Thresholding / Segmentation

Introduction to Imaging Processing presented by Media Cybernetics © Object splitting – using filters, or manually splitting by drawing lines between touching objects. Guard frame – when working on multiple fields side by side, we may need to specify that object touching the borders of the image. Pseudo-color – adds false color to the image to show changes in gray values not noticeable to the human eye. Pre Measurement Steps

Introduction to Imaging Processing presented by Media Cybernetics © Size (area, perimeter, length, etc) Shape (roundness, aspect ratio) Density / IOD Clusters Fractal Dimension Uniformity Once objects are identified, we are dealing then with a set of pixels, which are a set of numbers and thus we are able to measure anything as needed. Measurement Parameters

Introduction to Imaging Processing presented by Media Cybernetics © Statistical Measurement of Objects

Introduction to Imaging Processing presented by Media Cybernetics © Line Profile

Introduction to Imaging Processing presented by Media Cybernetics © Horizontal section Vertical section Curved section Thickness Measurements

Introduction to Imaging Processing presented by Media Cybernetics © Area Percentage Measurements

Introduction to Imaging Processing presented by Media Cybernetics © Colocalization Intensities in Time-Series Fluorescence Measurements

Introduction to Imaging Processing presented by Media Cybernetics © DDE data to Excel for further statistical analysis Create reports – single sheet with image, data, charts using a custom template creating a unified and consistent report mechanism for use department wide Data Collector – collection of analysis data from multiple images into a single space – which can then be used to DDE, or create reports Poster Printing – allows for taking a single image and printing it on multiple sheets of paper for presentation/poster sessions Annotation – all measurements can be placed onto the image as a layer so it does not interfere with future needs for analysis Data Output

Introduction to Imaging Processing presented by Media Cybernetics © Data Output

Introduction to Imaging Processing presented by Media Cybernetics © Original measured imageObjects sorted by e.g. area Sort Object in Gallery

Introduction to Imaging Processing presented by Media Cybernetics © Uses - Noise Removal

Introduction to Imaging Processing presented by Media Cybernetics © Dan Mulvihill Cell Developmental Biology Group University of Kent Raw ImageDeconvolvedThreshold Uses - Analysis

Introduction to Imaging Processing presented by Media Cybernetics © Uses - Visualization

Introduction to Imaging Processing presented by Media Cybernetics © Volume rendering Real Time Interaction Clipping Surface rendering Volume of Interest Three Dimensional Reconstruction

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