Lossy and lossless compression are two kinds of data compression techniques. Here in this article, you will get to learn about what is lossy and lossless compression, their differences, and uses.
So, let’s start with the basics.
What is Data Compression?
Data compression is the process of diminishing the storage size of any data or file so that it consumes less space on the disk. It is the technique of modifying, restructuring, encoding and converting the schema or instance of any data to reduce its size.
In simple words, it is converting the file in such a way that its size is reduced to a maximum extent. Data compressions is also known as bit-rate reduction or source coding.
Check the diagram below:
An example of an image that is converted or compressed to reduce its size without losing the ability to reconstruct the image.
Now, the question here is why there is a need for data compression?
There are two primary reasons for the same.
- Storage – it helps in reducing the size of data that is required to store it on the disk
- Time – saves time in data transmission as the size is reduced to an extent
You are getting the point!
Now coming back to the main topic, there are mainly two types of data compression techniques. Let’s discuss them.
Data Compression Techniques
Lossy Compression
Lossy compression is a technique that involves the elimination of a specific amount of data. It helps in reducing the file size to a great extent without any noticeable thing. Also, once the file is compressed, it cannot be restored back to its original form as the data from the file is significantly reduced. This technique is much more useful when the quality of the file is not essential. Additionally, it helps to save much space on the disk to store the data.
Lossy compression is not useful when the quality of the file is essential. Besides, if there’s any further analysis to be processed on the record, this method is not ideal. This method is generally used for audio and video compression, where there is a significant amount of data loss, and even users cannot recognize it.
Example of lossy compression: JPEG image
“Compressed image (left) shows blocking artifacts compared to the original image (right) as a result of the JPEG compression scheme used.”
Lossless Compression
Lossless compression is a technique that involves only a certain amount of elimination of data. This technique also helps in reducing the file size, but not to the greater extent as that of lossy compression. Instead, in this method, if the file is compressed, it can be restored back to its original form. Further, the quality of the data is not compromised; hence, the reduction in size is not much.
Lossless compression is not useful when you want reduced size for extra storage. Also, if there is any further analysis to be performed on the file, lossless compression is not beneficial. It is useful for maintaing the originality of files by eliminating only unwanted data. This technique is commonly used for text files, sensitive documents, and confidential information.
Example of lossless compression: PNG image
“The original image (left) is identical to the compressed image (right). It is represented by the identical graphs at the bottom that show the grey values for the pixels in each column is the same between the two images.”
Difference between Lossy and Lossless Compression
| Basis | Lossy Compression | Lossless Compression |
| Definition | Lossy compression is a technique that involves the elimination of a specific amount of data. It helps in reducing the file size to a great extent without any noticeable thing | Lossless compression is a technique that involves only a certain amount of elimination of data. This technique also helps in reducing the file size, but not to the greater extent |
| Compression Ratio | High | Low |
| File Quality | Low | High |
| Elimination of Data | Even the necessary data is also removed which isn’t noticeable | Only some specific amount of unwanted data is removed |
| Restoration | Cannot restore its original form | Can restore its original form |
| Loss of Information | This technique involves some loss of information | This technique doesn’t include any loss of information |
| Data Accommodation | More data accommodation | Less data accommodation |
| Distortion | Files are distorted | No distortion |
| Data holding capacity | More | Less |
| Algorithms Used | Transform coding, DCT, DWT, fractal compression, RSSMS | RLW, LZW, Arithmetic encoding, Huffman encoding, Shannon Fano coding |
| File Types | JPEG, GIF, MP3, MP4, MKV, OGG, etc. | RAW, BMP, PNG, WAV, FLAC, ALAC, etc. |
Which One to Use?
Although both are the types of data compression, each can be useful under different situations. Like, lossy compression helps in reducing the file size, which means it is helpful to those who have vast amounts of data stored on the database. So, this technique is useful in storing the data with a much-diminished size. Also, for webpages files of such lower size is beneficial for faster loading.
Further, this process doesn’t allow any after analysis of the data once the compression is completed. Also, the file cannot be restructured in its original form as it involves the loss of data.
Unlike lossy compression, lossless compression doesn’t involve any loss of data. Neither the quality of data is compromised, nor the size of data is excessively reduced. It keeps the original format so it can be restored, and further operation can be performed. This method is helpful for those who need to access the data back again without compromising its quality.
Final Words
Both lossy compression and lossless compression helps in the compression of data in their unique way. While lossy compression is useful to store data by compromising the data, lossless compression doesn’t. Lossless compression technique is beneficial for maintaing the originality of data, and lossy compression, on the other hand, doesn’t. Both the methods are helpful in database management, to identify and compress files accordingly.
If there’s any other query regarding data compression or both the techniques of data compression, then let us know in the comment box below.