A Novel Lossy Image Compression Method

Abstract

In this paper, we propose and implement a new lossy method to compress a digital image. We perform technique like quantization, smoothing before applying our novel, simple addition based technique to compress the image. The image is divided into set of 4*4 blocks. The results are good and comparable to JPEG compression algorithm, particularly when image quality is high. The compression ratio in the proposed method is high when adjacent pixel values in the image are close, which is usual in real images. (Abstract)

Lossless Compression Methods for Real-Time Images

“…Compression is, in general terms, data-encoding with a transformation method used to compress the size of a data file (Akhtar et al, 2014). Data/Image compression is required in applications with storage limitations, such as portable devices, as well as it is useful in digital image processing, because it helps to reduce any redundancy in the original image and reduce the consumption of expensive resources, since the original image is retrieved from the compressed image by decompressing it accordingly.…”

“…Data compression has many advantages; for instance, it helps to save bandwidth, storage space, cost and the time required for transmitting data between two places. Conversely, data compression has a downside, to reuse the data, the compressed data must be decompressed, which adds extra processing that may be detrimental to some applications (Arthur, 2012;Akhtar et al, 2014).…”

“…Both the lossy and lossless compression methods support many compression techniques. Run-length encoding, Huffman coding, and arithmetic coding are used for the lossless compression method, while dictionary-based algorithm, Lempel-Ziv-Welch (LZW), JPEG and MPEG are applied to the lossy compression method (Ashraf et al, 2006;Arthur, 2012;Akhtar et al, 2014).…”

“…Both the lossy and lossless compression methods support many compression techniques. Run-length encoding, Huffman coding, and arithmetic coding are used for the lossless compression method, while dictionary-based algorithm, Lempel-Ziv-Welch (LZW), JPEG and MPEG are applied to the lossy compression method (Ashraf et al, 2006;Arthur, 2012;Akhtar et al, 2014). However, in some cases two different compression methods are applied to compress the same image, to take the advantages of both by keeping the important details of the image as well as getting a high compression ratio, namely the hybrid compression method such as JPEG2000 (Firoozbakht, 2010).…”