Image Compression Research Paper

Image compression using super-resolution technique – A review

Sudeepti Dayal

T.I.E.I.T

Bhopal

Neelesh Gupta

T.I.E.I.T

Bhopal Neetu Sharma

T.I.E.I.T

Bhopal

ABSTRACT

With the rapid increasing demand of digital networks, people are likely to demand more and more accurate images which can be efficiently achieved using image compression. In image compression we remove the irrelevant data from the image keeping in mind that the data is stored in an adequate form. By doing this the data from the original image is sometimes is lost. Based on this, in the review paper we will be discussing the needs, its principle and various file formats of image compression. We will also focus on algorithms of image compression.

Keywords

Super resolution;

Image resolution describes the detail an image has. Higher the resolution, higher will be the image details. The resolution may be classified as: spatial resolution, pixel resolution, spectral resolution, temporal resolution, and radiometric resolution. In this context, spatial resolution is used to differentiate between the low resolution and the high resolution images. Spatial resolution is the number of independent pixel values per unit length.

Another resolution technique which can be used to acquire the image details is the super resolution (SR) technique.

Super resolution is a technique that modifies the resolution of an image. The technique converts low resolution (LR) images to high resolution (HR) which in turn increases the high frequency components and removes the blurriness caused by the low resolution camera. Thus this technique is used to reconstruct the original image with the high resolution image given a set of observed images at lower resolution.

2. NEED OF IMAGE COMPRESSION

In general, data compression is the process of reducing the amount of data required to represent a given quantity of information. The goal of image compression is to diminish the amount of data required to represent a digital

3. PRINCIPLE OF IMAGE OF COMPRESSION

The objective of image compression is to reduce the size of digital images to save storage space or transmission time. The image with dimensions 512*512*3 = 786,431 pixels requires only 41,909 bytes when compressed in JPEG format. The question that arises is how we can save the space while maintaining most of the content. The ratio of sizes tells us about the effectiveness the image. The term defining this is known as the compression ratio.

Compression ratio: Size of an original image Size of the compressed image

3.1 Compression algorithm

3.1.1 Lossless compression Lossless compression is a compression algorithm in which the original image can be reconstructed from the compressed image i.e. after compression, reconstructed image is numerically identical to the original image. Some of the image files formats use lossless compressions are PNG or GIF. Compressed

.

Fig 2 Lossless Compression

There are two techniques used in lossless compression. They are:-

1. Run Length Encoding

2. Huffman