Image stitching for mapping in Drone Programming - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is image stitching in the context of mapping?

Image stitching is the process of combining multiple overlapping photos taken by a drone into one large, seamless map or panorama.

beginner

Why do drones take overlapping images for stitching?

Overlapping images provide common points that stitching software uses to align and blend photos accurately, creating a continuous map without gaps.

intermediate

Name a common technique used to find matching points between images in stitching.

Feature detection algorithms like SIFT (Scale-Invariant Feature Transform) or ORB (Oriented FAST and Rotated BRIEF) find key points to match images.

intermediate

What role does GPS data play in drone image stitching?

GPS data helps roughly align images by providing location info, making stitching faster and more accurate by reducing guesswork.

advanced

What is a common challenge when stitching images for mapping?

Challenges include differences in lighting, moving objects, and lens distortion, which can cause visible seams or misalignments in the final map.

Why is image overlap important in drone mapping?

A It increases drone flight time

B It reduces the number of photos needed

C It makes images darker

D It helps software find matching points to align images

Overlap provides common features that stitching software uses to align and blend images seamlessly.

Which algorithm is commonly used to detect features for stitching?

A SIFT

B Bubble Sort

C Dijkstra's Algorithm

D Quick Sort

SIFT detects distinctive features in images to help match and align them during stitching.

How does GPS data assist in image stitching?

A By increasing image resolution

B By changing image colors

C By providing location info to roughly align images

D By controlling drone speed

GPS data gives approximate positions of images, helping stitching software align them faster and more accurately.

What problem can moving objects cause in image stitching?

A Visible seams or misalignments

B Faster stitching

C Better image quality

D Increased GPS accuracy

Moving objects can appear differently in overlapping images, causing stitching errors or visible seams.

What is the main goal of image stitching in drone mapping?

A Reduce drone battery usage

B Create one large, seamless map from many photos

C Make images black and white

D Increase drone speed

Image stitching combines multiple photos into a single continuous map for easier analysis and viewing.

Explain the basic steps involved in stitching drone images for mapping.

Think about how photos connect like puzzle pieces.

Describe common challenges faced during image stitching and how GPS data helps.

Consider what makes images hard to join and how location info assists.

Practice

1. What is the main purpose of image stitching in drone programming?

easy

A. To combine multiple drone photos into one large map

B. To control the drone's flight path

C. To improve the drone's battery life

D. To send live video feed to the operator

Solution

1. Step 1: Understand image stitching concept

   Image stitching is about joining many photos to create a bigger picture.

2. Step 2: Identify the main use in drone programming

   It helps create large maps from many drone images for better area coverage.

3. Final Answer:

   To combine multiple drone photos into one large map -> Option A

4. Quick Check:

   Image stitching = combine photos [OK]

Hint: Image stitching means joining photos into one big map [OK]

Common Mistakes:

• Confusing image stitching with drone control
• Thinking it improves battery life
• Mixing it with live video streaming

2. Which of the following is the correct way to start stitching images side by side in a drone program?

easy

A. stitch(images, method='side_by_side')

B. stitch(images, method='fly_path')

C. stitch(images, method='battery_save')

D. stitch(images, method='live_feed')

Solution

1. Step 1: Identify stitching method names

   Side by side stitching joins images horizontally or vertically.

2. Step 2: Match method to stitching task

   Only 'side_by_side' matches the stitching method; others relate to flight or battery.

3. Final Answer:

   stitch(images, method='side_by_side') -> Option A

4. Quick Check:

   Method 'side_by_side' = stitching images side by side [OK]

Hint: Use method='side_by_side' to join images simply [OK]

Common Mistakes:

• Using unrelated methods like 'fly_path' or 'battery_save'
• Confusing stitching method with drone flight commands
• Misspelling method names

3. Given the code snippet:

images = ['img1.jpg', 'img2.jpg', 'img3.jpg']
stitched_map = stitch(images, method='overlap')
print(len(stitched_map))

What will be the output if stitched_map is a combined image with 3 parts?

medium

A. 1

B. 3

C. 0

D. Error

Solution

1. Step 1: Understand the stitch function output

   Stitching combines images into one big image, so the result is a single image object.

2. Step 2: Check what len() returns on the stitched image

   Most image objects do not support len(), so calling len() will cause an error.

3. Final Answer:

   Error -> Option D

4. Quick Check:

   len() on image object causes error [OK]

Hint: len() on stitched image causes error [OK]

Common Mistakes:

• Assuming length equals number of input images
• Expecting len() to work on image object
• Confusing list length with image object length

4. The following code is meant to stitch images with overlap detection but throws an error:

images = ['a.jpg', 'b.jpg']
stitched = stitch(images, method='overlap')
stitched.show()

What is the likely cause of the error?

medium

A. The method 'overlap' is not supported

B. The show() method does not exist for stitched images

C. The stitch function requires images to be loaded, not file names

D. The images list is empty

Solution

1. Step 1: Check input type for stitch function

   Stitch usually needs image data, not just file names as strings.

2. Step 2: Identify error cause

   Passing file names without loading images causes errors when stitching or showing.

3. Final Answer:

   The stitch function requires images to be loaded, not file names -> Option C

4. Quick Check:

   Input must be loaded images, not file names [OK]

Hint: Load images before stitching, not just file names [OK]

Common Mistakes:

• Assuming method 'overlap' is invalid
• Thinking show() method is missing
• Ignoring that images list is not empty

5. You want to create a stitched map from drone images but only include images that have at least 30% overlap with the previous one. Which approach best applies this condition in your stitching code?

hard

A. Stitch all images first, then crop the map to overlapping areas

B. Filter images by overlap percentage before stitching using a function

C. Use method='side_by_side' to ignore overlap

D. Manually stitch images without any overlap checks

Solution

1. Step 1: Understand the overlap condition

   Only images with at least 30% overlap should be included in stitching.

2. Step 2: Choose the best way to apply this condition

   Filtering images before stitching ensures only suitable images are combined.

3. Final Answer:

   Filter images by overlap percentage before stitching using a function -> Option B

4. Quick Check:

   Filter first, then stitch = correct approach [OK]

Hint: Filter images by overlap before stitching [OK]

Common Mistakes:

• Stitching all images then cropping
• Ignoring overlap and stitching side by side
• Manual stitching without overlap checks