Image filtering in MATLAB - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to read an image file named 'image.jpg'.

MATLAB

img = imread('[1]');

Drag options to blanks, or click blank then click option'

A'image.png'

Bimage.jpg

C'image.jpg'

Dimage.png

Attempts:

3 left

💡 Hint

Common Mistakes

Forgetting the quotes around the filename.

Using the wrong file extension.

The imread function requires the filename as a string, so it must be enclosed in single quotes.

2fill in blank

medium

Complete the code to convert the image to grayscale.

MATLAB

gray_img = [1](img);

Drag options to blanks, or click blank then click option'

Argb2gray

Bimadjust

Crgb2hsv

Dim2bw

Attempts:

3 left

💡 Hint

Common Mistakes

Using im2bw which converts to binary, not grayscale.

Using imadjust which adjusts contrast.

The rgb2gray function converts a color image to grayscale.

3fill in blank

hard

Fix the error in the code to apply a 3x3 averaging filter to the grayscale image.

MATLAB

h = fspecial('[1]', [3 3]);
filtered_img = imfilter(gray_img, h);

Drag options to blanks, or click blank then click option'

Aaverage

Bmedian

Caveragefilter

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'averagefilter' which is not a valid filter type.

Using 'median' which is a different filter.

The correct filter type for averaging in fspecial is 'average'.

4fill in blank

hard

Fill both blanks to create a Gaussian filter with standard deviation 0.5 and apply it to the image.

MATLAB

h = fspecial('[1]', [2]);
filtered_img = imfilter(img, h);

Drag options to blanks, or click blank then click option'

Agaussian

B[3 3]

C0.5

D[5 5]

Attempts:

3 left

💡 Hint

Common Mistakes

Putting the standard deviation where the size should be.

Using incorrect filter type strings.

The fspecial function needs 'gaussian' as the filter type and the size of the filter as a vector like [3 3]. The standard deviation can be specified as a third argument if needed.

5fill in blank

hard

Fill all three blanks to create a Laplacian filter, apply it, and display the result.

MATLAB

h = fspecial('[1]');
filtered_img = imfilter([2], h);
imshow([3]);

Drag options to blanks, or click blank then click option'

Alaplacian

Bgray_img

Cfiltered_img

Dgaussian

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'gaussian' instead of 'laplacian' for the filter.

Displaying the original image instead of the filtered one.

The Laplacian filter is created with 'laplacian', applied to the grayscale image, and the filtered image is displayed.

Practice

1. What is the main purpose of applying an image filter using a kernel in MATLAB?

easy

A. To convert the image to grayscale

B. To modify the image by emphasizing or reducing certain features

C. To increase the image file size

D. To change the image file format

Solution

1. Step 1: Understand what a kernel does

   A kernel is a small matrix used to process an image by changing pixel values based on neighbors.

2. Step 2: Identify the effect of filtering

   Filtering modifies the image to highlight edges, blur, or sharpen features, not file format or size.

3. Final Answer:

   To modify the image by emphasizing or reducing certain features -> Option B

4. Quick Check:

   Image filtering changes features = D [OK]

Hint: Filters change image features, not file type or size [OK]

Common Mistakes:

• Confusing filtering with file format conversion
• Thinking filtering changes image size
• Assuming filtering only converts to grayscale

2. Which of the following is the correct syntax to apply a filter kernel h to an image img using MATLAB's imfilter function?

easy

A. filtered_img = filter(h, img);

B. filtered_img = filter(img, h);

C. filtered_img = imfilter(h, img);

D. filtered_img = imfilter(img, h);

Solution

1. Step 1: Recall MATLAB's imfilter syntax

   The correct syntax is imfilter(image, kernel), where the image is first and kernel second.

2. Step 2: Check each option

   filtered_img = imfilter(img, h); matches the correct syntax. Options B and D use 'filter' which is incorrect. filtered_img = imfilter(h, img); reverses arguments.

3. Final Answer:

   filtered_img = imfilter(img, h); -> Option D

4. Quick Check:

   imfilter(image, kernel) = A [OK]

Hint: imfilter(image, kernel) is the correct order [OK]

Common Mistakes:

• Using 'filter' instead of 'imfilter'
• Swapping image and kernel arguments
• Missing semicolon or parentheses

3. Given the following MATLAB code:

img = [1 2 3; 4 5 6; 7 8 9];
h = [1 0 -1; 1 0 -1; 1 0 -1];
result = imfilter(img, h, 'replicate');

What is the value of result(2,2)?

medium

A. 0

B. 3

C. 6

D. 9

Solution

1. Step 1: Understand the filter and padding

   The kernel h detects vertical edges. 'replicate' pads edges by repeating border values.

2. Step 2: Calculate convolution at (2,2)

   Neighborhood of (2,2):
   1 2 3
   4 5 6
   7 8 9
   Apply kernel:
   (1*1)+(0*2)+(-1*3)+(1*4)+(0*5)+(-1*6)+(1*7)+(0*8)+(-1*9) = 1+0-3+4+0-6+7+0-9 = (1-3)+(4-6)+(7-9) = -2 -2 -2 = -6
   But imfilter flips kernel, so actual sum is 6.

3. Final Answer:

   6 -> Option C

4. Quick Check:

   imfilter result center = 6 [OK]

Hint: Remember imfilter flips kernel before applying [OK]

Common Mistakes:

• Not flipping the kernel before convolution
• Ignoring padding method 'replicate'
• Calculating sum incorrectly

4. Consider this MATLAB code snippet:

img = imread('peppers.png');
h = fspecial('average', 3);
filtered_img = imfilter(img, h, 'same');

What is the error in this code?

medium

A. No error; the code runs correctly

B. imfilter requires grayscale images only

C. The kernel size in fspecial must be odd

D. The 'same' option is invalid for imfilter

Solution

1. Step 1: Check fspecial usage

   fspecial('average', 3) creates a 3x3 averaging filter, which is valid.

2. Step 2: Check imfilter usage

   imfilter supports RGB images and 'same' option returns output same size as input.

3. Final Answer:

   No error; the code runs correctly -> Option A

4. Quick Check:

   fspecial + imfilter with 'same' = A [OK]

Hint: imfilter works with color images and 'same' option [OK]

Common Mistakes:

• Assuming imfilter only works on grayscale
• Thinking 'same' is invalid option
• Believing kernel size must be odd but 3 is odd and valid

5. You want to sharpen an image img in MATLAB by combining the original image with a filtered version using the Laplacian kernel h = fspecial('laplacian', 0.2);. Which code snippet correctly applies this sharpening?

hard

A. sharpened = img - imfilter(img, h, 'replicate');

B. sharpened = img + imfilter(img, h, 'replicate');

C. sharpened = imfilter(img, h, 'replicate') - img;

D. sharpened = imfilter(img, h, 'replicate') + img * 0.2;

Solution

1. Step 1: Understand Laplacian sharpening

   Sharpening = original image minus the Laplacian filtered image to enhance edges.

2. Step 2: Match code to formula

   sharpened = img - imfilter(img, h, 'replicate'); subtracts the filtered image from original, correctly applying sharpening.

3. Final Answer:

   sharpened = img - imfilter(img, h, 'replicate'); -> Option A

4. Quick Check:

   Sharpen = img - Laplacian filtered img = B [OK]

Hint: Sharpen by subtracting Laplacian filtered image [OK]

Common Mistakes:

• Adding instead of subtracting Laplacian result
• Multiplying original image incorrectly
• Confusing Laplacian with averaging filter