Digtial Image Processing, Spring ECES 682 Digital Image Processing Oleh Tretiak ECE Department Drexel University

Digtial Image Processing, Spring About the Course Instructor: Oleh Tretiak, Bossone 607, , Office hours: M 2-4, Tu 2-4, or by appointment Textbook: Rafael C. Gonzalez and Richard E. Woods, Digital Image Processing (Second Edition), Prentice Hall, 2002 Web site: ece.drexel.edu/courses/ECE-S682  Site contains syllabus, assignments, solutions, exams, etc  We will also use webct (reachable through Drexel One or via for grade distribution  Also see textbook website, imageprocessingplace.com

Digtial Image Processing, Spring This Weeks Lecture Image Enhancement in the Spatial Domain  Gray level transformations  Histogram processing  Arithmetic/Logic operations  Spatial filtering  Smoothing  Sharpening Matlab image processing  Image datatypes  Image display  Color maps

Digtial Image Processing, Spring Intensity Scale What does ‘image intensity’ mean? In technical images, image intensity is reflects an objective quantity  In astronomy, intensity reflects energy per sterradian  In transmission microscopy, intensity is a function of amount of absorbing material on a ray passing through an object In most images, image intensity is a feature that allows us to infer the presence of objects in a scene. For human vision, the image is reflected by ‘intensity’ and ‘color’. Most of the time, intensity is much more important than color

Digtial Image Processing, Spring General Framework We compute a new image from an original image The most basic transformation is g(x, y) = T(f(x, y)) where f(x, y) is the gray value of the input image pixel, g(x, y) is the gray value of the input image pixel at the same locations, and T() is a function of a single (real) variable.

Digtial Image Processing, Spring Conventions: Digital Images Left: Digital image. Note unusual (x, y) convention. Below: Examples of gray-value transformations.

Digtial Image Processing, Spring Basic Gray Level Transformations Negative Log Power law Piecewise linear Bit slicing

Digtial Image Processing, Spring Histogram Processing The histogram Histogram processing Histogram equalization  Global  Local Histogram matching Local means, variances

Digtial Image Processing, Spring Arithmetic/Logical Operations Logical operations: x is a 4 bit number)  AND(x, 1111) = x  AND(x, 0000) = 0  OR(x, 1111) = 1111  OR(x, 1111) = x Subtraction: change detection Addition: Image averaging

Digtial Image Processing, Spring Spatial Filtering How big should a, b be? What do we do at edges? What are we trying to accomplish?  Smoothing  Edge detection Alternate notation:

Digtial Image Processing, Spring Smoothing Masks Smoothing masks are normally adjusted to preserve average value (∑w i = 1)

Digtial Image Processing, Spring Order Statistics Filters R = median(z 1, … z n ) R = max (z 1, … z n ) R = min (z 1, … z n )

Digtial Image Processing, Spring Sharpening Filters One-dimensional Two-dimensional (Laplacian)

Digtial Image Processing, Spring Laplacian Masks

Digtial Image Processing, Spring Image Sharpening (a)Orignal Image, (b)Laplacian, (c) Laplacian – scaled, (d) Original plus Laplacian (a) (d)(c) (b)

Digtial Image Processing, Spring Unsharp Masking/High Boosting Unsharp masking is a technique developed in film chemical processing. An out-of-focus image was subtracted from the original.

Digtial Image Processing, Spring First Derivative Enhancement There is no first derivative linear filter that is not direction-dependent Magnitude of the gradient is independent of direction

Digtial Image Processing, Spring Some Implementations Upper masks: Roberts filter. Lower masks: Sobel Filter

Digtial Image Processing, Spring Other Examples Unsharp masking with rank filters Product masks (image times Sobel) Combine with power-law transformation...

Digtial Image Processing, Spring Objective value (intensity) Subjective (perceived) value Mach Bands

Digtial Image Processing, Spring The circles have the same objective intensity.

Digtial Image Processing, Spring

Digtial Image Processing, Spring