CS654: Digital Image Analysis

Lecture 17: Image Enhancement

Recap of Lecture 16

• Mask processing

• Spatial filtering

• Averaging

• Differentiation

• Correlation

• Convolution

Outline of Lecture 17

• Image enhancement

• Dynamic range

• Point processing

• Contrast stretching

• Intensity level slicing

Introduction

• Improve the quality of an image as perceived by human being

• Can be performed at both spatial and frequency domain

• Different types of enhancement

• Noise suppression

• Increase contrast

• Sharpen or smoothen image feature

• Emphasise

• Display and analysis

Common techniques

Image enhancement

Point processing Spatial operation Transform operation

Pseudocoloring

• Contrast stretching• Noise clipping• Window slicing• Histogram modeling

• Noise smoothing• Median filtering• Unsharp masking• Filtering

• Linear filter• Root filter• Homomorphic filter

Dynamic Range

• The ratio between the maximum and minimum measurable light intensities

• In the real world, one never encounters true white or black

Image: cambridgeincolour

ILLUMINANCE & REFLECTIVITY

• Both contribute to the dynamic range of a scene

• Illuminance to specify only incident light

• Vast variation possible for incident light

Dynamic Range of Camera

Black Level(Limited by Noise)

White Level(Saturated)

Darker White Level(Low Capacity)

Cavity Array Light Cavities

Image: cambridgeincolour

Human eye

Weber ratio as a function of intensity

HDR Images, Posterization

Images: Gonzalez & Woods, 3rd edition

Intensity transformation

𝑔 (𝑥 , 𝑦 )=𝑇 ( 𝑓 (𝑥 , 𝑦 ))

: Transformed image

: Input image

: Transformation function

Images: Gonzalez & Woods, 3rd edition

𝑠=𝑇 (𝑟 )neighbourhood

Point processing

Point processing

Images: Gonzalez & Woods, 3rd edition

Contrast stretching function

0 255

255

Thresholding function

0 255

255

Intensity transformation: Negative

𝐿−𝑟𝑠=¿Transformation function

Images: Gonzalez & Woods, 3rd edition

Intensity transformation: Log-transform

𝑠=𝑐𝑙𝑜𝑔 (1+𝑟 ) ;𝑟 ≥0Transformation function

• Maps narrow low intensity to wider range of intensity

• Compresses the dynamic range of images

Images: Gonzalez & Woods, 3rd edition

Intensity transformation: Gamma

𝑠=𝑐𝑟𝛾Transformation function

• Fractional value maps narrow low intensity to wider range of intensity

• Higher value maps narrow low intensity to wider range of intensity

Images: Gonzalez & Woods, 3rd edition

Gamma correction: Display

Images: Gonzalez & Woods, 3rd edition

Gamma corrected image as viewed in monitor

Gamma correction

Gamma corrected image

Original image Input image as viewed in monitor

Gamma correction; Dark to light

Images: Gonzalez & Woods, 3rd edition

Orig

inal

imag

e

0.6

0.4 0.3

Gamma correction: light to dark

Images: Gonzalez & Woods, 3rd edition

3.0

4.0 5.0

Contrast stretching

Images: Gonzalez & Woods, 3rd edition

𝛼 𝛽 𝛾

𝑠={ 𝛼𝑟 ;0≤𝑟 ≤𝑟 1𝛽 (𝑟 −𝑎)+𝑠1 ;𝑟1≤𝑟 ≤𝑟 2𝛾 (𝑟−𝑏)+𝑠2;𝑏≤𝑟 ≤ 𝐿

𝒓𝟏 𝒓𝟐

Spans the full range of intensity level

𝑟1=𝑠1 ,𝑟 2=𝑠2 Linear

𝑟1=𝑟2 ,𝑠1=0 , 𝑠2=𝐿−1Thresholding

𝒔𝟏

𝒔𝟐

Contrast stretching

Input image Contrast stretched image

Thresholded image

Images: Gonzalez & Woods, 3rd edition

Gray-level slicing

• Highlight a specific range of gray values

Without background

𝑠={ 𝐿 ; 𝐴≤𝑟 ≤𝐵0 ; h𝑜𝑡 𝑒𝑟𝑤𝑖𝑠𝑒

With background

𝑠={ 𝐿; 𝐴≤𝑟 ≤𝐵𝑟 ; h𝑜𝑡 𝑒𝑟𝑤𝑖𝑠𝑒

Example

Input image Without background With background

Bit plane slicing

Bit plane representation of 8 bit images

1 2

4 5

7 8

3

6

Reconstruction of images

8+7

8+7+6

8+7+6+5

Thank youNext lecture: Histogram Processing