JPEG Graphics File Format - Essay Example

The standard uses lossy compression techniques that result in image quality getting lost after compression which can never be recovered. Hence, the artist needs to be an expert to decide the most appropriate trade-off between the image quality and the file size. This short essay hereby introduces the compression techniques of JPEG and the decision-making guidelines when deciding the compression ratio. [Wallace, 2001. pp3-6]

Introduction of JPEG Compression Techniques:

The JPEG compression algorithm involves three stages – Colour Space Conversion (Red-Green-Blue triplets mapped to Luminance-Chrominance Blue-Chrominance Red triplets), Segmentation into 8x8 pixel blocks, and Discrete Cosine Transformation (image transformation from the spatial domain to frequency domain representation) encoding stage that includes Quantization (sorting the output waveform of DCT), Zigzag Scan (sorting the frequency coefficients from low to high), and Entropy Coding (Huffman Coding and Arithmetic Coding).


The encoding and decoding algorithms for JPEG images are shown in Figures 1 and 2 respectively. Compression is used to reduce the file sizes such that they can be used on web pages or documentation or any other lightweight graphics applications. The 8x8 blocks of source images are first shifted from unsigned integers to signed integers and then applied to the Forward Discrete Cosine Transformer (FDCT). To decode the compressed image to achieve the 8x8 blocks again, they are applied to the entropy decoder whereby the output is taken out from the Inverse Discrete Cosine Transformer (IDCT). The final processing step of the DCT encoder is the entropy coding that achieves additional compression by encoding the quantized DCT coefficients based on statistical characteristics. There are two types of Entropy Coding methods – Huffman coding and Arithmetic coding. Huffman coding requires one or more sets of Huffman code tables whereas Arithmetic coding doesn’t require any external tables (although statistical conditioning tables as inputs can improve coding efficiency). The quantization stage of the JPEG algorithm results in loss of information, thus making the JPEG standard a lossy compression technique. [Wallace, 2001. pp3-6]
0.25 to 0.5 bits per pixel: The output image shall possess moderate to good quality
0.5 to 0.75 bits per pixel: The output image shall possess good to very good quality
0.75 to 1.5 bits per pixel: The output image shall possess excellent quality
1.5 to 2.0 bits per pixel: The output image shall be practically non-distinguishable from the original image
The improved version of the original JPEG technology is JPEG 2000 which provides better rate-distortion performance than the original JPEG standard. JPEG 2000 ensures better image quality compared to JPEG at any given bit rate but the best improvements can be observed at very low or very high bit rates. JPEG 2000 possesses a mathematically lossless mode for reduction of storage requirement to 2:1 but is still able to regenerate the original image information. What is more significantly important here is “Visual Lossless Compression” which means that even a trained eye is unable to differentiate between the original & compressed images. JPEG 2000 achieves “Visual Lossless Compressions” at ratios ranging from 10:1 to 20:1. Visually Lossy compressions occur at 50:1 to 100:1 suitable for web pages. However, it should be noted that fundamentally JPEG 2000 compressions do lead to loss of data after compression at any ratio. Visually, JPEG 2000 results in a soft blur at high-frequency areas and hence is very much suitable for creating videos even at high compressions ratio because the human eye is often unable to mark this difference in moving images. Practically, JPEG 2000 is accepted as the official format for high-quality images for Digital Cameras, Digital Cinema, Medical Imaging, High-Quality Broadcasts, Live Broadcast Streaming, and other key sectors. JPEG 2000 is however not suitable for compressing diagram-type images like a Digital Elevation Model (Maps) given that it is not space efficient for a desired quality as against more space-efficient graphics algorithms like Portable Network Graphics (PNG).
JPEG 2000 bit-streams comprise of four dimensions – resolution, quality, spatial location, and component. These dimensions are defined under various combinations for various applications. An example combination is presented in the figure below for Digital Cinema Distribution:
Conclusion:
In this short essay, the compression techniques of JPEG and the enhancements achieved in JPEG 2000 are presented. The discussions include mapping of bits per pixel and compression ratios with the output quality. The essay also introduced the target application areas of JPEG 2000 (the successor and improved version of JPEG). Read More