JPEG compressor using MATLAB

Published on 01 Jul 2021. Written by Mukka Mugdha

ABSTRACT

Creating, editing and designing images as per our style is a major priority in now a day’s lifestyle. Images with larger size make it difficult to store them. As the camera sensor produces an original image with a large size. To handle this situation and to store these images with small size, there should be a size density method. The JPEG, an image compression method took a major process to compress the image and store them. For this MATLAB hardware output is used as a quick way to study the JPEG system.

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SLNOTE
INTRODUCTION

JPEG means joint photographic experts group. The JPEG is the most popular method and it is used in multiple devices, such as digital cameras. JPEG process is best suited for photo and accurate scenes. In Lossy compression method can be used in images where some unwanted details are removed to save the storage space. And in lossless compression system, it opens bitstream to identify the original bit. To get the correct image the transformation of coding, discrete cosine transform and wavelet transform takes place. Transform coding founds an important part of modern image/video processing applications. The transform coding depends on the principle that the quality in the image display, and linked with the adjacent quality. Similarly, in the video transmission system, these are linked with the quality of their neighbours. Transform converts the sub-blocks to secondary image data, thereby reducing inter-frame joblessness. 

SLLATEST
The transform is a lossless operation, so if we reverse the transform we can get the original image. This redundancy is called “mental vision redundancy”. Discrete cosine transform has been widely arranged by modern video coding standards such as MPEG. The discrete cosine transform is a method for converting a signal component into basic components. The discrete cosine transform work for linking the image data. After the linking, each transforms number can be coded individually without losing density efficiency. It works from left most corners to right-most corners or top to bottom. Each block starts reducing by quantization process. 

Entropy coding is a lossless data. It includes image components arranged in "zigzag" order by using run-length encoding (RLE) procedure together with a similar occurrence, and also it uses Huffman coding. Wavelet transform is a method of representing time-frequency signals from the wavelet transform. It is called wavelet base done varying frequency and finite time. Wavelet transforms used in multiple purposes. Wavelet transforms has both irreversible method and reversible method.

CONCLUSION

This explains the JPEG image compression process of encoding. It can be obtained by using a discrete cosine transform method. This Discrete cosine transform method removes unnecessary information, so there is a need to introduce discrete cosine transform method for compressing. By using jpeg compression method we can easily store more number of images as it reduces the size of the image. 

SLDYK
Kit required to develop JPEG compressor using MATLAB:

• MATLAB

Technologies you will learn by working on JPEG compressor using MATLAB:

• MATLAB

Any Questions?