Disadvantages Of Image Compression

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When we think about the world of digital, there is a more information. Therefore, When dealing with this, we have to face difficulties. so we have need to store, retrieve and process this information in efficient way. In digital image processing, image compression plays an important role. Image compression is used in number of application and it plays important role for efficient transmission and storage of images. Image compression is the process in which data required to the represent an image is reduced to obtain minimum storage space. Image Compression improves the performance of a digital system by reducing cost of image storage. 1.2 Principle Behind Image Compression: The original image consists of three types of redundancies. If…show more content…
Still image is further divided into binary and continuous tone.JPEG is a continuous-Tone still image. JPEG: As shown in figure (1) JPEG is a continuous-Tone still image. The Joint Photography Expert Group proposed JPEG in1986. JPEG is an important standard for image compression.JPEG is a most popular, continuous tone still image standard in image compression. The JPG file is an extension for JPEG. This JPG file extension is widely used in a internet image compression. 3.2 Architecture of the system Figure 2 JPEG Image…show more content…
Huffman decoding has same architecture used for encoding. Same variable Length Code table is used. The output of Huffman encoding given to the decoding block to obtain decodable code .The encoding code is taken and search for corresponding run/value combinations. When the corresponding run/value combination is found, it is send as a output. Then Huffman starts decoding next input. To obtain less complexity, use of VLC table is necessary. De-quantization: The decoded output of Huffman decoding is provided to the de-quantization. De-quantization is a inverse process of quantization. The output from this process is obtain by using multiplication operation The output values of Huffman decoding is multiply with the quantization value provided in quantization table. IDCT: IDCT is a reverse process of DCT. In IDCT, Loeffler’s algorithm used in a reverse manner. Steps For IDCT using Loeffler’s butterfly Structure: Stage 1 : All inputs are multiplied with uniform coefficients. Stage 2 : Separate even and odd coefficient. Stage 3 : Again separate even and odd coefficients. Stage 4: Apply regular butterfly

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