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Topic 5. Introduction to Digital Image Interpretation and Analysis

Division of Geodetic Engineering College of Engineering and Information Technology Caraga State University

GE 113 – REMOTE SENSING

Lecturer: Engr. Jojene R. Santillan [email protected]

Lecture Notes in GE 113: Remote Sensing TOPIC 5. INTRODUCTION TO DIGITAL IMAGE INTERPRETATION AND ANALYSIS

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Outline

• Overview of Digital Image Interpretation and Analysis – Different computer-

assisted procedures

– Comparison between

manual versus digital image interpretation and analysis

– Advantages and

Disadvantages of Digital Image Processing

Lecture Notes in GE 113: Remote Sensing TOPIC 5. INTRODUCTION TO DIGITAL IMAGE INTERPRETATION AND ANALYSIS

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Expected Outcomes

• The students would be able to:

– Learn the concept behind digital image interpretation and analysis

– Know the differences between digital and manual image interpretation and analysis

– Identify the various computer-assisted procedures of manipulation and interpretation of digital images

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PART 1. OVERVIEW OF DIGITAL IMAGE INTERPRETATION AND ANALYSIS

Lecture Notes in GE 113: Remote Sensing TOPIC 5. INTRODUCTION TO DIGITAL IMAGE INTERPRETATION AND ANALYSIS

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• Digital image interpretation and analysis involves the manipulation and interpretation of digital images with the aid of a computer.

• Also called “digital image processing”

Lecture Notes in GE 113: Remote Sensing TOPIC 5. INTRODUCTION TO DIGITAL IMAGE INTERPRETATION AND ANALYSIS

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Digital Image Processing

• Central Idea:

– Digital image is fed into a computer one pixel at a time, using image processing software/program

– Using the software/program, data is inserted into an equation or series of equations, and then store the results of the computation for each pixel

– Results form a new digital image data that maybe displayed or recorded in pictorial format or may itself be further manipulated by additional programs

Lecture Notes in GE 113: Remote Sensing TOPIC 5. INTRODUCTION TO DIGITAL IMAGE INTERPRETATION AND ANALYSIS

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Digital Image Processing Procedures (after Lillesand, et al., 2008)

1. Image rectification and restoration

2. Image enhancement

3. Image classification

4. Data merging and GIS integration

5. Hyperspectral image analysis

6. Biophysical modeling

7. Image transmission and compression

• All of these are computer-assisted procedures.

Lecture Notes in GE 113: Remote Sensing TOPIC 5. INTRODUCTION TO DIGITAL IMAGE INTERPRETATION AND ANALYSIS

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Image Rectification and Restoration (1) (to be discussed in detail in Topic 6)

• Operations that aim to correct distorted or degraded image data to create a more faithful representation of the original scene.

• Often termed “Image pre-processing” operations/procedures:

– They are normally done to the image data prior to any further manipulation and analysis

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Image Rectification and Restoration (2) (to be discussed in detail in Topic 6)

• Typically involves initial processing of raw image data to:

– Correct for geometric distortions

• i.e., to ensure that all pixels in the image are correctly geo-referenced makes it possible to conduct accurate point, line and area measurements in the image

– Calibrate/correct the data radiometrically:

• E.g., to convert DN to absolute radiance values

– Eliminate noise present in the data

Lecture Notes in GE 113: Remote Sensing TOPIC 5. INTRODUCTION TO DIGITAL IMAGE INTERPRETATION AND ANALYSIS

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Image Rectification and Restoration (3) (to be discussed in detail in Topic 6)

• Example:

Raw Image Rectified Image

Lecture Notes in GE 113: Remote Sensing TOPIC 5. INTRODUCTION TO DIGITAL IMAGE INTERPRETATION AND ANALYSIS

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Image Rectification and Restoration (4) (to be discussed in detail in Topic 6)

• Example:

Raw Image Restored Image (haze corrected)

© www.rese.ch

Lecture Notes in GE 113: Remote Sensing TOPIC 5. INTRODUCTION TO DIGITAL IMAGE INTERPRETATION AND ANALYSIS

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Image Rectification and Restoration (4) (to be discussed in detail in Topic 6)

• Example:

Raw Image Restored Image (haze corrected)

© https://www.researchgate.net/profile/James_Green33

Lecture Notes in GE 113: Remote Sensing TOPIC 5. INTRODUCTION TO DIGITAL IMAGE INTERPRETATION AND ANALYSIS

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Image Enhancement (1) (to be discussed in detail in Topic 7)

• These procedures are applied in order to more effectively display or record the data for subsequent visual interpretation

• Involves techniques that increase the visual distinctions between features in a scene

• The objective is to create “new” images from the original image data in order to increase the amount of information that can be visually interpreted from the data

Lecture Notes in GE 113: Remote Sensing TOPIC 5. INTRODUCTION TO DIGITAL IMAGE INTERPRETATION AND ANALYSIS

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Image Enhancement (2) (to be discussed in detail in Topic 7)

• Common image enhancement procedures:

– Contrast manipulation

• Gray-level thresholding

• Level slicing

• Contrast stretching

– Spatial feature manipulation

• Spatial filtering/convolution

• Edge enhancement

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Image Enhancement Example 1: (to be discussed in detail in Topic 7)

Raw Image Contrast-enhanced Image

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Image Enhancement Example 2: (to be discussed in detail in Topic 7)

Raw Image Contrast-enhanced and Spatially-Filtered Image to enhance edges

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Image Classification (1) (to be discussed in detail in Topic 8)

• Operations that replace visual analysis of the image data with quantitative techniques for automating the identification of features in a scene

• Involves: – Analysis of multispectral image data – Application of statistically-based decision rules for

determining the identity of each pixel in an image

• The intent of the classification process is to categorize all pixels in a digital image into one of several land-cover classes or “themes”

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Image Classification Example (to be discussed in detail in Topic 8)

© CSU Phil-LiDAR 2

Input Image Automatically Classified Image

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Manual versus Digital Image Interpretation and Analysis

Manual

• Requires experience

• Simple to implement using inexpensive equipment.

• Uses brightness and spatial content of the image.

• Usually single channel data or three channels at most.

• Subjective, concrete, qualitative.

Digital

• Requires specialized training

• Complex to implement; requires expensive software

• Relies chiefly upon brightness and spectral content; use of spatial content is usually limited

• Frequent use of data from several channels

• Objective, abstract (“theoretical/conceptual”), quantitative.

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Digital Image Processing Advantages and Disadvantages

Advantages

• Cost effective – Especially for large

geographical areas

• Repetitive interpretations/analysis can be done

• Produces consistent results

• Allows Simultaneous interpretations of several channels

• Allows the use of complex interpretation algorithms

• Faster than manual visual image interpretation

Disadvantages • Expensive for small areas • Start-up costs may be high

(due to the need for an image processing software) – but free, open source software are currently available

• Accuracy may be difficult to evaluate

• Requires standard image formats

• Preprocessing may be required

• May require large support staff (especially if done for several hundreds of images)

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Note:

• Each of the three digital image processing procedures will be discussed in the next topics.

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• Questions or clarifications?

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References/Further Reading

• Lillesand, T. M., Kiefer, R. W., & Chipman, J. W. (2008). Remote Sensing and Image Interpretation 6th Edition. United States of America: John Wiley & Sons, Inc.

• Online Tutorial: Fundamentals of Remote Sensing – “Digital Image Processing”. Available at http://www.nrcan.gc.ca/earth-sciences/geomatics/satellite-imagery-air-photos/satellite-imagery-products/educational-resources/9279