Image Compression Techniques
Abstract:In this chapter,the basic principle of a commonly ud technique for image compression called transform coding will be described.After a short summary of uful image formats,we shall describe two commonly ud image coding standards, the JPEG.
Keyword:image compression,JPEG standards.
To u the computer for image analysis to achieve the required results of the technology.Also known as image processing.
The basic content of image processing generally refers to digital image processing. Image processing technology,including the main elements of image compression,and enhanced recovery,match,describe and identify three parts.
Digital images are compresd by the image of an enormous amount of data,a typical digital image is usually from500×500or1000×1000pixels composition.If the image is dynamic,is its greater volume of data.Therefore image compression for image storage and transmission are very necessary.
There were two types of compression algorithm,yet that is really similar to the methods and means.The
most common non-distortion of space or time compression from adjacent pixels on the value of the poor,and then encoded.Run code is such compression code example.Approximate image compression algorithm ud to exchange most of the way,such as the fast Fourier transform images or discrete cosine transform.Well-known,as the international image compression standard JPEG and MPEG are similar to a compression algorithm.The former ud for still images, which ud to moving images.They have been chip.
Image enhancement and recovery image enhancement goal is to improve the quality of images,such as increasing contrast,remove the ambiguity and noi,that geometric distortion;image restoration is known in the vague assumption that the model or the noi,trying to estimate the original image of a Technology.
Image enhancement by the methods ud can be divided into the frequency domain law and space domain law.The former of the two-dimensional image as a signal, bad on their two-dimensional Fourier transform the signal enhancement.Low pass filter(that is,only low-frequency signals through),can remove the map of noi,a high pass filter,can enhance the edge of high-frequency signals,and so on,so that the fuzzy picture has become clear.A reprentative of the space domain algorithm for a local law and the average median filter(from the middle of local jurisdictions adjacent
pixels)Act,they can be ud for the removal or weakening of noi.
Image format
Real world images,such as color images,usually contain different components.For color images reprented in the RGB color system,there will be three component images corresponding to the R,G,and B components.Since the RGB color component is relatively uniform in terms of quantization,they are frequently employed in color nsors with each component being quantized to 8bits.From the trichromatic theory of color mixture,most colors can be reprented by three properly chon primary colors.The RGB color primary,which contains the red,green and blue colors,is most popular for illuminating sources.The CMY primary is very common for reflecting light sources and they are frequently employed in printing (the CMYK format).
Other than the RGB system,there are a number of color coordinate systems such as YIQ,YUV,XYZ,UVW,U*V*W*,L*a*b*,and L*[236,127].Since human visual system (HVS)is less nsitive to high-frequency chrominance information,the YCbCr color system is commonly ud in image coding.The RGB image can be converted to the YCbCr color space using the following formula
0.2990.5870.1140.1690.3310.500. 0.5000.4190.081Y R Cb G Cr B ⎡⎤⎡⎤⎡⎤⎢⎥⎢⎥⎢⎥=−−⎢⎥⎢⎥⎢⎥⎢⎥⎢⎥⎢⎥−−⎣⎦⎣⎦⎣⎦
Transform coding of images
黄素梅For simplicity,we will consider grey scale images first.For color images,the original image is usually converted to the YCrCb-(4:2:0)format and the same technique for using the Y component image is applied to the Cr and Cb component images.The image to be encoded is first divided into (N*N)non-overlapping blocks,and each block is transformed by a 2D transformation such as the 2D discrete cosine transform (DCT).The basic idea of transform coding is to pack most of the energy of the image block into a few transform coefficients.This process is usually called energy compaction.The transform coefficients are then adaptively quantized.The quantized coefficients and other auxiliary information will be entropy coded and packed according to a certain format into a bit-stream for transmission or storage.At the decoder,the bit-stream is decoded to recover the various information.
Since the amplitudes of the transform coefficients usually differ considerably from each other,it is advantageous to u a different number of quantizer levels (i.e.,bits)for each transform coefficients.This problem is called the bit allocation problem.Quantization
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There are a number of methods to encode the transform coefficients.For example,a popular method is to employ scalar quantization followed by run-length and entropy
coding.Alternatively,VQ or embedded zero-tree coding can be applied[331].For simplicity,we only describe the first approach,which is employed in the JPEG Baline coding.Similar methods are also employed in other video coding standards. Most coding standards require the image pixels be preprocesd to have a mean of zero.For RGB color space,all color components have a mean value of128(8-bit /pixel).In YCbCr color space,the Y component has an average value of128,while the chrominance components have an average value of zero.
JPEG standard
The JPEG(Joint Photographic Experts Group)standard is an ISO/IEC international standard(10918-1)for Digital compression and coding of continuous-tone still images.It is also an ITU standard known as ITU-T Recommendation T.81.To satisfy different requirements in practical applications,the standard defines four modes of operation:艺术魅力
黄酒怎么做Sequential DCT-bad:This mode is bad on DCT-bad transform coding with a block size of(8x8)for each color component.The transform coefficients are runlength and entropy coded.A subs
et of this mode is the Baline Mode,which is an implementation with a minimum t of requirements for a JPEG compliant decoder.
Progressive DCT-bad:This mode is similar to the quential DCT-bad algorithm,except that the quantized coefficients are transmitted in multiple scans.By partially decoding the transmitted data,this mode allows a rough preview of the transmitted image to be obtained at the decoder having a low transmission bandwidth. Lossless:This mode is intended for lossless coding of digital images.It us a prediction approach,where the input image pixel is predicted from adjacent encoded pixels.The prediction residual is then entropy-coded.
Hierarchical:This mode provides spatial scalability and encodes the input image into a quence of increasing resolution.The lowest resolution image can be encoded using either the lossy or lossless techniques in other mode,while the residuals are coded using the lossy or DCT-bad modes.吃栗子
JPEG supports multiple component images.For color images,the input image is usually in RGB and other formats like luminance and chrominance reprentation (YUV,YCbCr),etc.The color space conversion process is not part of the standard, but most codecs employ the YCbCr system becau the chrominance components can be decimated by a factor of two in the horizontal and vertical dimensions to achieve a better compression performance.
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Either Huffman or arithmetic coding techniques can be ud in the JPEG modes (except the Baline mode,where Huffman coding is mandatory)for entropy coding. The arithmetic coding techniques usually perform better than the Huffman coding in JPEG,while the latter is simpler to implement.For Huffman coding,up to4AC and2 DC tables can be specified.The input image to JPEG may have from I to65,535lines and from1to65,535pixels per line.Each pixel may have from1to255color components except for progressive mode,where at most four components are allowed. For the DCT modes,each component pixel is an8or12bits unsigned integer,except for the Baline mode,where8-bit precision is allowed.For the lossless mode,a
range from2to16bits is supported.
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