Image compression is a data compression technique that is mainly applied to digital images. This technique is practiced to reduce the size and space for image storage and transmission. As compared to generic data compression practices, image compression delivers images that are visually appealing and retain their statistical properties.
What is digital image compression?
Digital Image Compression 4.4 Introduction Lossless compression techniques These are used when raw image data are difficult to obtain or contain vital information that may be destroyed by compression, e.g. in medical diagnostic imaging.
What is a typical compression ratio in image processing?
•A typical compression ratio around 10 or(10:1) indicates that 90% (R D =0.9) of the data in the first data set is redundant. EE-583: Digital Image Processing
What is the central concept in image compression?
•Data redundancy is the central concept in image compression and can be mathematically defined. EE-583: Digital Image Processing Prepared By: Dr. Hasan Demirel, PhD
What kind of compression can be obtained for a binary image?
uSubstantial compression can be obtained for binary or bitmap images (moderate compression for raw greyscale images). LZW compression É. Pitas Digital Image Processing Algorithms
What are the types of image compression?
There are two kinds of image compression methods - lossless vs lossy.
Why is image compression needed?
The objective of image compression is to reduce irrelevance and redundancy of the image data to be able to store or transmit data in an efficient form. It is concerned with minimizing the number of bits required to represent an image. Image compression may be lossy or lossless.
What are the basic steps of image compression?
JPEG Compression algorithm has five main basic steps.RGB color space to YCbCr color space Conversion.Preprocessing for DCT transformation.DCT Transformation.Co-efficient Quantization.Lossless Encoding.
What are different compression methods?
There are two main types of compression: lossy and lossless.
What is the best compression method for images?
The DCT is sometimes referred to as "DCT-II" in the context of a family of discrete cosine transforms (see discrete cosine transform). It is generally the most efficient form of image compression. DCT is used in JPEG, the most popular lossy format, and the more recent HEIF.
What is lossy and lossless compression?
With lossless compression, every bit of data originally in a file remains after it is uncompressed, and all the information is restored. Lossy compression reduces a file by permanently eliminating certain information, especially redundant information.
What is the need for image compression?
1. Unit V. Image Compression Two mark Questions 1. What is the need for image compression? In terms of storage, the capacity of a storage device can be effectively increased with methods that compress a body of data on its way to a storage device and decompresses it when it is retrieved. In terms of communications, the bandwidth of a digital communication link can be effectively increased by compressing data at the sending end and decompressing data at the receiving end. At any given time, the ability of the Internet to transfer data is fixed. Thus, if data can effectively be compressed wherever possible, significant improvements of data throughput can be achieved. Many files can be combined into one compressed document making sending easier. 2. What is run length coding? Run-length Encoding, or RLE is a technique used to reduce the size of a repeating string of characters. This repeating string is called a run; typically RLE encodes a run of symbols into two bytes, a count and a symbol. RLE can compress any type of data regardless of its information content, but the content of data to be compressed affects the compression ratio. Compression is normally measured with the compression ratio. 3. What are the different compression methods? The different compression methods are, i. Run Length Encoding (RLE) ii. Arithmetic coding iii. Huffman coding and iv. Transform coding 4. Define compression ratio. Compression ratio is defined as the ratio of original size of the image to compressed size of the image. It is given as Compression Ratio = original size / compressed size: 1
What is lossless compression?
Lossless compression can recover the exact original data after compression. It is used mainly for compressing database records, spreadsheets or word processing files, where exact replication of the original is essential.
How can bandwidth be increased?
In terms of communications, the bandwidth of a digital communication link can be effectively increased by compressing data at the sending end and decompressing data at the receiving end. At any given time, the ability of the Internet to transfer data is fixed.
How to eliminate redundancy in a picture?
1) Devising an alternative representation of the image in which its interpixel redundant are reduced. 2) Coding the representation to eliminate coding redundancy 20.Define Huffman coding. Huffman coding is a popular technique for removing coding redundancy.
What is digital image compression?
Digital image compression has been a research topic for many years and a number of image compression standards have been created for different applications [1, 2 ]. The JPEG2000 is intended to provide rate-distortion and subjective image quality performance superior to existing standards, as well as to supply functionality [ 3]. However, JPEG2000 does not provide the most relevant characteristics of the human visual system, since for removing information in order to compress the image mainly information theory criteria are applied. This information removal introduces artifacts to the image that are visible at high compression rates, because of many pixels with high perceptual significance have been discarded. Hence, an advanced model is necessary that removes information according to perceptual criteria, preserving the pixels with high perceptual relevance regardless of the numerical information. The Chromatic Induction Wavelet Model presents some perceptual concepts that can be suitable for it. Both contrast band-pass filtering (CBPF) and JPEG2000 use wavelet transform. CBPF uses it in order to generate an approximation to how every pixel is perceived from a certain distance taking into account the value of its neighboring pixels. By contrast, JPEG2000 applies a perceptual criterion for all coefficients in a certain spatial frequency independently of the values of its surrounding ones. In other words, JPEG2000 performs a global transformation of wavelet coefficients, while CBPF performs a local one. CBPF attenuates the details that the human visual system is not able to perceive, enhances those that are perceptually relevant, and produces an approximation of the image that the brain visual cortex perceives. At long distances, the lack of information does not produce the well-known compression artifacts; rather it is presented as a softened version, where the details with high perceptual value remain (e.g., some edges).
Which is better, JPEG or JPEG LS?
The decompressed output of the “baseline JPEG” can be visually indistinguishable from the original image. JPEG-LS gives better compression than original JPEG, but still nowhere near what one can get with a lossy method.
What happens if a pixel has a colour B?
The idea of this approach extends the image compression principles and concludes that if the current pixel has colour B (or W) then black (or white) pixels seen in the past ( or those that will be found in future) tend to have the same immediate neighbours.
Is MPEG good for video?
MPEG, which is good for compressing existing videos, is not well suited for our interactive setting, in which each image is generated on the fly and is displayed in real time. Using MPEG is not completely impossible, but the overhead would be too high to make both the encoding and the decoding efficient in software.
Is image compression lossy or lossless?
Image compression may be lossy or lossless. Lossless compression is preferred for archival purposes and often for medical imaging, technical drawings, clip art, or comics. Lossy compression methods, especially when used at low bit rates, introduce compression artifacts.
What is compressed data?
Meta information. Compressed data may contain information about the image which may be used to categorize, search, or browse images. Such information may include color and texture statistics, small preview images, and author or copyright information. Processing power.
What is lossy compression?
Lossy compression methods, especially when used at low bit rates, introduce compression artifacts. Lossy methods are especially suitable for natural images such as photographs in applications where minor (sometimes imperceptible) loss of fidelity is acceptable to achieve a substantial reduction in bit rate.
What is DCT in JPEG?
DCT is used in JPEG, the most popular lossy format, and the more recent HEIF. The more recently developed wavelet transform is also used extensively, followed by quantization and entropy coding. Reducing the color space to the most common colors in the image.
When was JPEG 2000 created?
The JPEG 2000 standard was developed from 1997 to 2000 by a JPEG committee chaired by Touradj Ebrahimi (later the JPEG president). In contrast to the DCT algorithm used by the original JPEG format, JPEG 2000 instead uses discrete wavelet transform (DWT) algorithms.
When did JPEG become a file format?
DCT compression became the basis for JPEG, which was introduced by the Joint Photographic Experts Group (JPEG) in 1992. JPEG compresses images down to much smaller file sizes, and has become the most widely used image file format.
When was the deflate algorithm introduced?
It is used in the GIF format, introduced in 1987 . DEFLATE, a lossless compression algorithm developed by Phil Katz and specified in 1996, is used in the Portable Network Graphics (PNG) format. Wavelet coding, the use of wavelet transforms in image compression, began after the development of DCT coding.
What is resolution progressive?
Resolution progressive: First encode a lower image resolution; then encode the difference to higher resolutions. Component progressive: First encode grey-scale version; then adding full color. Region of interest coding. Certain parts of the image are encoded with higher quality than others.
Why Do We Need Image Compression?
Transforming The Image
- What is a transformation(Mathematically): It a function that maps from one domain(vector space) to another domain(other vector space). Assume, T is a transform, f(t):X->X’ is a function then, T(f(t)) is called the transform of the function. We generally carry out the transformation of the function from one vector space to the other because when we do that in the newly projected vec…
Quantization
- The process quantization is a vital step in which the various levels of intensity are grouped into a particular level based on the mathematical function defined on the pixels. Generally, the newer level is determined by taking a fixed filter size of “m” and dividing each of the “m” terms of the filter and rounding it its closest integer and again multiplying with “m”.
Symbol Encoding
- The symbol stage involves where the distinct characters involved in the image are encoded in a way that the no. of bits required to represent a character is optimal based on the frequency of the character’s occurrence. In simple terms, In this stage codewords are generated for the different characters present. By doing so we aim to reduce the no. of bits required to represent the intensi…
Overview
Image compression is a type of data compression applied to digital images, to reduce their cost for storage or transmission. Algorithms may take advantage of visual perception and the statistical properties of image data to provide superior results compared with generic data compression methods which are used for other digital data.
Lossy and lossless image compression
Image compression may be lossy or lossless. Lossless compression is preferred for archival purposes and often for medical imaging, technical drawings, clip art, or comics. Lossy compression methods, especially when used at low bit rates, introduce compression artifacts. Lossy methods are especially suitable for natural images such as photographs in applications where minor (sometimes imperceptible) loss of fidelity is acceptable to achieve a substantial re…
Other properties
The best image quality at a given compression rate (or bit rate) is the main goal of image compression, however, there are other important properties of image compression schemes:
Scalability generally refers to a quality reduction achieved by manipulation of the bitstream or file (without decompression and re-compression). Other names for scalability are progressive coding or embedded bitstreams. Despite its contrary nature, scalability also may be found in lossless c…
History
Entropy coding started in the 1940s with the introduction of Shannon–Fano coding, the basis for Huffman coding which was developed in 1950. Transform coding dates back to the late 1960s, with the introduction of fast Fourier transform (FFT) coding in 1968 and the Hadamard transform in 1969.
An important development in image data compression was the discrete cosine transform (DCT), a lossy …
External links
• Image compression – lecture from MIT OpenCourseWare
• Image Coding Fundamentals
• A study about image compression – with basics, comparing different compression methods like JPEG2000, JPEG and JPEG XR / HD Photo