Computer Graphics Questions
There are several types of image compression algorithms used in computer graphics. Some of the commonly used ones include:
1. Lossless Compression: This algorithm reduces the file size of an image without losing any information. Examples of lossless compression algorithms are Run-Length Encoding (RLE), Huffman coding, and Lempel-Ziv-Welch (LZW) compression.
2. Lossy Compression: This algorithm reduces the file size by discarding some information that is less noticeable to the human eye. Examples of lossy compression algorithms are Discrete Cosine Transform (DCT), Joint Photographic Experts Group (JPEG) compression, and Wavelet-based compression.
3. Fractal Compression: This algorithm uses mathematical techniques to represent an image as a set of self-replicating patterns called fractals. Fractal compression is particularly effective for compressing natural images with repetitive patterns.
4. Vector Quantization: This algorithm represents an image as a collection of vectors and then quantizes them to reduce the file size. Vector quantization is commonly used in image compression standards like the Graphics Interchange Format (GIF).
5. Transform Coding: This algorithm applies mathematical transformations to an image, such as Fourier Transform or Discrete Wavelet Transform, to convert it into a frequency domain representation. The transformed coefficients are then quantized and encoded to achieve compression.
These are just a few examples of the different types of image compression algorithms used in computer graphics. Each algorithm has its own advantages and disadvantages, and the choice of algorithm depends on factors such as the desired compression ratio, image quality requirements, and computational resources available.