]] is the process of reducing the size of an image file, making it more manageable for storage and transmission. There are two main types of image compression techniques: and .
Lossy compression is a technique that allows for significant reduction of file size but at the cost of some loss. This method achieves compression by discarding unnecessary details and information that might not be noticeable to the human eye. , , and are common formats that use lossy compression.
plays a vital role in image compression as it determines the amount of data used to represent each pixel. Higher bitrates result in higher image quality but larger file sizes.
The Discrete Cosine Transform () is an essential technique used in image compression. It breaks down the image into different frequency components, allowing for more compression. is then applied to further reduce the amount of data by grouping similar values together.
Run-Length Encoding (RLE) is a simple yet efficient compression algorithm. It replaces sequences of repeated data values with a count of the value and the value itself. This method is often used in lossless compression schemes.
In conclusion, image compression techniques, such as lossy compression and lossless compression, are used to reduce file size while maintaining acceptable image quality. Formats like JPEG, GIF, and PNG employ different compression algorithms to achieve efficient data representation. Bitrate, DCT, Quantization, and are essential components in the compression process that help achieve efficient image compression.
