|BASIC||Loss compression is the family of data coding methods that uses imprecise estimates to represent the content.||Lossless compression is a group of data compression algorithms that allows the original data to be accurately reconstructed from the compressed data.|
|Algorithm||Coding by transformation, DCT, DWT, fractal compression, RSSMS.||RLW, LZW, arithmetic coding, Huffman coding, Shannon Fano coding.|
|Used in||Images, audio and video.||Text or program, images and sound.|
|Request||JPEG, GUI, MP3, MP4, OGG, H-264, MKV, etc.||RAW, BMP, PNG, WAV, FLAC, ALAC, etc.|
|Channel data storage capacity.||Ms||Less compared to the method with loss|
Loss compression definition
The method of loss compression delete a certain amount of data that is not noticed. This technique does not allow a file to be restored in its original form, but significantly reduces the size. Loss compression technique is beneficial if data quality is not your priority. It slightly degrades the quality of the file or data, but it is convenient when one wants to send or store the data. This type of data compression is used for organic data such as audio signals and images.
Loss compression technique
- Coding by transformation : This method transforms the pixels that are mapped into a representation in non-associated pixels. The new size is usually smaller than the original size and reduces the redundancy of the representation.
- Transformed discrete cosine (DCT) : This is the most used image compression technique. JPEG process centers around DCT. The DCT process divides the images into different parts of the frequencies. In the quantification step, where compression occurs basically, the less important frequencies are rejected. And the critical frequencies are retained so that the image can be obtained in the decompression process. The reconstructed image may contain some distortion.
- Discrete Wavelet Transformation (DWT) : Provides a time and frequency location simultaneously and can be used to decompose a signal into component wavelets.
Definition of compression without loss
The method of compression without loss It is capable of reconstituting the original form of the data. The quality of the data is not compromised. This technique allows a file to restore its original form. The lossless compression can be applied to any file format and can improve the performance of the compression ratio.
Lossless compression technique
- Run Length Encoding (RLE) : This technique reduces the frequency of the symbols that are repeated in a chain by using a special marker at the beginning of the symbol.
- Lempel-Ziv-Welch (LZW) : This technique also works similarly to the RLE technique and searches for the repeated strings or words and stores them in variables. Then use a pointer instead of the string and the pointer is the variable in which the string is stored.
- Huffman coding : This technique handles the compression of ASCII character data. Build a complete binary tree for several symbols after calculating the probability of each symbol and placing it in descending order.
Key differences between compression with loss and compression without loss
- Compression with loss eliminates non-useful part of the data, which is undetectable, while compression without loss reconstructs the exact data.
- Lossless compression can reduce the size of the data to a low degree. On the other hand, compression with loss may decrease file size to a greater extent.
- The quality of the data is degraded in the case of a compression with loss, while the loss of data does not degrade the quality of the data.
- In lossy technique, the channel accommodates more data. Conversely, the channel has a smaller amount of data in case of technique without loss.
Loss compression can achieve a high level of data compression compared to lossless compression. Compression without loss does not degrade data quality, in contrast, the loss of data quality degrades. The lost technique cannot be implemented in all file types because it works by deleting a part of the (redundant) data that is not possible in the case of text.