Data Compression Ratio Analyzer

Input Statistics

Character Count

0

Unique Characters

0

Original Size (UTF-8)

0 bytes

Original Size (Bits)

0 bits

Algorithm Comparison

Algorithm	Compressed Size	Compression Ratio	Space Saved	Efficiency

Recommendation

Run-Length Encoding (RLE) Analysis

How RLE Works: Consecutive identical characters are encoded as [count][character]

Example: "AAABBB" → "3A3B"

Encoded Output:

Original Length

0

Compressed Length

0

Compression Ratio

0%

Runs Detected

0

Character Frequency Distribution

Character	ASCII/Unicode	Frequency	Percentage

Huffman Encoding Preview

Huffman Coding: Variable-length codes based on character frequency. More frequent characters get shorter codes.

Character	Frequency	Code	Code Length

About Compression Algorithms

Run-Length Encoding (RLE)

Best for: Data with many consecutive repeated characters (images, simple graphics)

How it works: Replaces runs of identical characters with a count and the character

Example: "WWWWWWWW" → "8W"

Weakness: Can increase size if data has few repeating characters

Huffman Encoding

Best for: Text and general data with varying character frequencies

How it works: Builds a binary tree based on character frequencies, assigns shorter codes to frequent characters

Example: Frequent 'e' might be "10", rare 'z' might be "110010"

Advantage: Optimal prefix-free code for known frequency distribution

LZ77 (Dictionary-Based)

Best for: Text with repeated phrases or patterns

How it works: References previously seen sequences using (distance, length) pairs

Example: "the cat and the dog" - second "the" references first occurrence

Used in: ZIP, GZIP, PNG compression

Arithmetic Encoding

Best for: Maximum compression efficiency

How it works: Represents entire message as a single number in range [0,1)

Advantage: Can achieve better compression than Huffman

Used in: JPEG 2000, H.264 video compression

Understanding Compression Metrics

Compression Ratio:

Ratio = (Compressed Size / Original Size) × 100%

Lower is better. 50% means compressed to half the original size.

Space Saved:

Space Saved = Original Size - Compressed Size

Shows absolute reduction in bytes or bits.

Compression Efficiency:

Efficiency = ((Original Size - Compressed Size) / Original Size) × 100%

Higher is better. 50% efficiency means you saved half the space.

Important Notes:

These calculations are simplified and don't include header/metadata overhead
Real-world compression includes additional data for decompression
Some algorithms may increase size for certain inputs
Best algorithm depends on your specific data characteristics

When to Use Each Algorithm

Use RLE when:

Data has long runs of identical values (bitmap images, fax)
Speed is critical (RLE is very fast)
Simple implementation is needed

Use Huffman when:

Character frequencies vary significantly
You need guaranteed decompression
Working with text or mixed data

Use Dictionary-Based (LZ77) when:

Data has repeated patterns or phrases
Working with natural language text
Need good general-purpose compression

Use Arithmetic when:

Maximum compression is critical
Computational cost is acceptable
Working with multimedia (images, video, audio)

Input Text