---
title: "Computer image processing with example"
subject: "Multimedia System"
chapter: 3
key: "semester_8/multimedia_system:computer-image-processing"
source: https://www.bctengineer.com/q/semester_8/multimedia_system/computer-image-processing
site: BCT Engineering
---

# Computer image processing with example

Multimedia System · Chapter 3: Images and Graphics

- Asked in: 2072 Magh, 6 marks
- Video: [Introduction to Digital Image Processing 🔥🔥](https://www.youtube.com/watch?v=aduibjn0ehM) — Perfect Computer Engineer
- Answer checked by Claude Opus 5.5 (high effort) on 2026-10-14
- Page: https://www.bctengineer.com/q/semester_8/multimedia_system/computer-image-processing
- Whole chapter: https://www.bctengineer.com/md/semester_8/multimedia_system/chapter-3

## Question

Explain the computer image processing with example.

## Short answer

Computer image processing applies algorithms to digital images for enhancement, analysis or compression. Typical steps: acquisition, pre-processing, enhancement, segmentation, representation. Example: a 3×3 averaging filter reduces noise by replacing a spike pixel 200 with average 62 from its neighbours.

## Answer

**Computer image processing** means applying algorithms to digital images to improve them, extract information from them or prepare them for storage and transmission. An image is a 2-D array of pixel values, and processing converts one array into another (or into data).

#### Main areas (Steinmetz)

- **Image synthesis:** creating images from descriptions or models.
- **Image analysis:** extracting features and recognising objects.
- **Image transmission:** sending images efficiently over a network.

#### Typical processing steps

```text
 Acquire -> Pre-process -> Enhance -> Segment -> Represent
 (scan)     (noise,         (contrast,  (find      & output
             geometry)       sharpen)    objects)
```

1. **Acquisition:** capture or scan the picture and digitise it.
2. **Pre-processing / restoration:** remove noise and blur, correct geometric distortion.
3. **Enhancement:** improve visibility by contrast stretching, histogram equalisation, sharpening or smoothing filters.
4. **Segmentation:** separate objects from background by thresholding or edge detection.
5. **Representation and description:** express objects with boundaries or features.
6. **Compression and output:** store, print or display.

#### Operations by type

- **Point operations:** each pixel changed on its own (brightness, contrast, negative).
- **Neighbourhood (filter) operations:** new value from the pixel and its neighbours using a mask (convolution): blurring, sharpening, edge detection.
- **Geometric operations:** rotate, scale, crop.

#### Example: smoothing with a 3 x 3 averaging mask

A pixel with value 200 surrounded by neighbours 10, 20, 30, 40, 50, 60, 70, 80 (noise spike at the centre) becomes (10+20+30+40+200+50+60+70+80)/9 = 560/9 = about 62. The spike is reduced, so noise is removed but edges blur slightly.

Another example: photo of a faded old document is improved by histogram equalisation to enhance contrast, then thresholded to black and white for OCR.

## Check yourself

The answer's key points as multiple-choice questions, with the correct option and why.

1. What does computer image processing mean?
   A. Only printing digital pictures on paper
   B. Applying algorithms to digital images (2-D arrays) to improve them, extract information or prepare them for storage and transmission
   C. Drawing pictures by hand and scanning them
   D. Converting video into audio
   Answer: B. Processing converts one pixel array into another (or into data) to enhance, analyse or transmit the image. (Key point: Definition)

2. Which is the correct order of typical processing steps?
   A. Segmentation, acquisition, enhancement, pre-processing
   B. Enhancement, acquisition, segmentation, pre-processing
   C. Acquisition, pre-processing, enhancement, segmentation
   D. Acquisition, segmentation, pre-processing, enhancement
   Answer: C. The picture is acquired, cleaned (noise, geometry), enhanced, then segmented into objects, then represented and output. (Key point: Order of steps)

3. Which type of operation computes a new pixel value from the pixel and its neighbours using a mask?
   A. Point operation
   B. Geometric operation
   C. Neighbourhood (filter) operation
   D. Acquisition operation
   Answer: C. Neighbourhood operations use a mask (convolution) over surrounding pixels, e.g. blurring, sharpening, edge detection. Point operations change each pixel alone. (Key point: Neighbourhood operations)

4. A 3x3 averaging mask is applied to a centre pixel 200 with neighbours 10, 20, 30, 40, 50, 60, 70, 80. What is the result and effect?
   A. About 62; the noise spike is reduced but edges blur slightly
   B. About 200; nothing changes
   C. About 110; edges become sharper
   D. About 62; edges become much sharper
   Answer: A. (10+20+30+40+200+50+60+70+80)/9 = 560/9, about 62. Smoothing removes the spike but blurs edges a little. (Key point: Averaging example)

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