Computer Processing

How a Computer Works: The Science of Images, Pixels, Binary, and Processing

Look carefully at the images below. The first image is a part of a painting. The second image is an AI‑generated realistic version of that painting, and its size is 1.81 megabytes. In the third image, an image editor shows that the second image has a total resolution of 928 × 1146. That means the image contains: 928 × 1146 = 1,063,488 pixels. The number of pixels depends on the quality of the image – the more pixels, the better the image quality. This image has 72 pixels per inch, but it can be higher, such as 300 or more. The higher the value, the sharper the image will be, and even when zoomed in, the pixels won’t separate or make the image look broken. The last two images were added just like that, without any particular reason. A pixel is even smaller than the tip of a pin.

Notice that the newly generated second image contains more than one million pixels.
Each pixel contains three color values – R (Red), G (Green), B (Blue). Each value is a number between 0 and 255. For example:

• A pixel from a dark part of the hair could be: 0, 0, 0 (pure black)
• A pixel from the white part of the blouse could be: 255, 255, 255 (pure white)
• Similarly, a pixel from another area could be: 145, 31, 212 – which represents a different color
  

These numbers appear as colors on the screen – meaning the processor processes these values and sends them to the monitor, and the monitor displays them as colors. When you move your mouse, thousands of pixels around the cursor position are constantly changing their values.

🔢 Numbers to Binary: The Language of Computers

A computer does not directly understand 0–255, or A, B, C, D, 2, 3, or anything else. It understands only 0 and 1 – that is, binary.

Example:

• The binary value of 2: 00000010
• The binary value of 255: 11111111

Because 255 is the maximum value in 8 bits.

The computer reads these 0s and 1s as electrical signals –

• If there is electrical charge = 1
• If there is no charge = 0

This is the most fundamental language of computers. Think of an electric bulb: when you switch it on, electrical charge reaches the bulb – that is 1. When you switch it off, there is no charge – that is 0. In this way, a computer repeats this process of sending and removing electrical signals millions of times per second, allowing us to solve extremely complex problems.

In the first paragraph, you saw that the AI‑generated second image is 1.81 megabytes. We know:

Computer storage units are based on binary (1024):

• 8 bits = 1 byte
• 1024 bytes = 1 kilobyte (KB)
• 1024 kilobytes = 1 megabyte (MB)
• 1024 megabytes = 1 gigabyte (GB)
• 1024 gigabytes = 1 terabyte (TB)

Based on that, the image is 1.81 MB ≈ 1,897,924 bytes

A standard RGB pixel = 24 bits = 3 bytes

Based on that, the first 256 bytes of the 1,897,924‑byte image look like this in binary – the computer’s language:

11111111 11011000 11111111 11100000 00000000 00010000 01001010 01000110
00000000 00000001 00000001 00000001 00000000 00000000 11111111 11100001
00000000 00010000 01001010 01000110 01000101 01011000 01001001 01000110
00000000 00000001 00000001 00000001 00000000 00000000 11111111 11100010
00000000 00010000 01001010 01000110 01000101 01011000 01001001 01000110
00000000 00000001 00000001 00000001 00000000 00000000 11111111 11100011
11110000 11000000 00000000 00000000 00000000 00000000 00000000 00000000
11111111 11110100 00000000 00010000 01001010 01000110 01000101 01011000
01001001 01000110 00000000 00000001 00000001 00000001 00000000 00000000
11111111 11110101 11110000 11000000 00000000 00000000 00000000 00000000
00000000 00000000 11111111 11110110 00000000 00010000 01001010 01000110
01000101 01011000 01001001 01000110 00000000 00000001 00000001 00000001
00000000 00000000 11111111 11110111 11110000 11000000 00000000 00000000
00000000 00000000 00000000 00000000 11111111 11111000 00000000 00010000
01001010 01000110 01000101 01011000 01001001 01000110 00000000 00000001
00000001 00000001 00000000 00000000 11111111 11111001 11110000 11000000
00000000 00000000 00000000 00000000 00000000 00000000 11111111 11111010
00000000 00010000 01001010 01000110 01000101 01011000 01001001 01000110
00000000 00000001 00000001 00000001 00000000 00000000 11111111 11111011
11110000 11000000 00000000 00000000 00000000 00000000 00000000 00000000
11111111 11111100 00000000 00010000 01001010 01000110 01000101 01011000
01001001 01000110 00000000 00000001 00000001 00000001 00000000 00000000
11111111 11111101 11110000 11000000 00000000 00000000 00000000 00000000
00000000 00000000 11111111 11111110 00000000 00010000 01001010 01000110
01000101 01011000 01001001 01000110 00000000 00000001 00000001 00000001
00000000 00000000 11111111 11111111

If you save the image, this space will be added to the hard disk; if you don’t save it, it will be added to RAM.

🧠 Why is a computer called a “simple machine”?

A computer is actually very simple – it only understands two states: on or off, 1 or 0.
But on top of this simplicity stands incredible complexity. All the complex problem‑solving that computers or mobile phones do is built on these two numbers.

To process a single image, a computer has to:

• Read millions of pixels
• Analyze the three color values of each pixel
• Convert each value into binary
• Then use that data for computation, transformation, filtering, rendering, etc.

All of this happens within nanoseconds.

🤖 When AI transforms an image

Here, an AI has transformed a painting into a realistic portrait of a woman – to perform such a task, the CPU or GPU has to perform billions of calculations.

What the AI model has to do:

• Analyze every pixel of the image
• Detect color, texture, shading, and shapes
• Infer human facial structure, lighting, shadows, and skin tone
• Then generate a new, realistic image

During this whole process, the following happens:

• Matrix multiplication
• Convolution operations
• Layer‑to‑layer computation in neural networks
• Backpropagation and application of weights

All of this is ultimately based on 0s and 1s.

What we see is: “An image created with one click!”
But in the background, what happens is:

• Billions of calculations
• Thousands of parameters being updated
• Computation after computation

This is the speed and power of computers.

⚙️ How a computer works: step‑by‑step breakdown

1️⃣ Input
You provide an image, give a command, or open a file – that is the input.

2️⃣ Processing
The CPU or GPU breaks the input down into tiny binary pieces.

Then the computation begins.

3️⃣ Storage
The data is stored temporarily or permanently in RAM or storage.

4️⃣ Output
Finally, what appears on the screen is:

• Images
• Videos
• Text
• Or any other result

This entire cycle runs billions of times per second. Everything happens so fast that we feel like it’s happening instantly!

🧩 Why are computers so fast?

Because:

• A CPU contains billions of transistors
• Each transistor represents either 0 or 1
• They all work together
• They can perform billions of operations per second

A human can make 2–3 decisions in one second.
A computer can make billions (100 crore+) of decisions in the same time.

🖼️ Let’s understand with an example image

The second image:

• Total pixels: 1,063,488
• Each pixel has 3 color values
• Each value is 8-bit (0–255)

That means the whole image contains:

More than 25 million bits.
These are what the computer reads, analyzes, and modifies.

Computers look simple – just 0 and 1

But on top of this simplicity, we’ve built:

• Image processing
• Video rendering
• AI
• Internet
• Gaming
• Space research
• Medical imaging
• Language translation
• Robotics
  

For us, transforming an image with AI feels like “one click” – but for the computer, it is the result of billions of calculations. That’s why a computer is, at the same time, both simple and incredibly complex.