Introduction. 1. Two Dimensional Systems and Mathematical Preliminaries. 2. Image Perception. 3. Image Sampling and Quantization. 4. Image Transforms. 5. Image Representation by Stochastic Models. 6. Image Enhancement. 7. Image Filtering and Restoration. 8. Image Analysis and Computer Vision. 9. Image Reconstruction From Projections. 10. Image Data Compression.

Fundamentals of digital image processing

The problem of rotation-, scale-, and translation-invariant recognition of images is discussed. A set of rotation-invariant features are introduced. They are the magnitudes of a set of orthogonal complex moments of the image known as Zernike moments. Scale and translation invariance are obtained by first normalizing the image with respect to these parameters using its regular geometrical moments. A systematic reconstruction-based method for deciding the highest-order Zernike moments required in a classification problem is developed. The quality of the reconstructed image is examined through its comparison to the original one. The orthogonality property of the Zernike moments, which simplifies the process of image reconstruction, make the suggest feature selection approach practical. Features of each order can also be weighted according to their contribution to the reconstruction process. The superiority of Zernike moment features over regular moments and moment invariants was experimentally verified. >

Invariant image recognition by Zernike moments

Digital audio, video, images, and documents are flying through cyberspace to their respective owners. Unfortunately, along the way, individuals may choose to intervene and take this content for themselves. Digital watermarking and steganography technology greatly reduces the instances of this by limiting or eliminating the ability of third parties to decipher the content that he has taken. The many techiniques of digital watermarking (embedding a code) and steganography (hiding information) continue to evolve as applications that necessitate them do the same. The authors of this second edition provide an update on the framework for applying these techniques that they provided researchers and professionals in the first well-received edition. Steganography and steganalysis (the art of detecting hidden information) have been added to a robust treatment of digital watermarking, as many in each field research and deal with the other. New material includes watermarking with side information, QIM, and dirty-paper codes. The revision and inclusion of new material by these influential authors has created a must-own book for anyone in this profession.

*This new edition now contains essential information on steganalysis and steganography
*New concepts and new applications including QIM introduced
*Digital watermark embedding is given a complete update with new processes and applications

Digital Watermarking and Steganography

Research and development of OCR systems are considered from a historical point of view. The historical development of commercial systems is included. Both template matching and structure analysis approaches to R&D are considered. It is noted that the two approaches are coming closer and tending to merge. Commercial products are divided into three generations, for each of which some representative OCR systems are chosen and described in some detail. Some comments are made on recent techniques applied to OCR, such as expert systems and neural networks, and some open problems are indicated. The authors' views and hopes regarding future trends are presented. >

Historical review of OCR research and development

Presents a new method to match a 2D image to a translated, rotated and scaled reference image. The approach consists of two steps: the calculation of a Fourier-Mellin invariant (FMI) descriptor for each image to be matched, and the matching of the FMI descriptors. The FMI descriptor is translation invariant, and represents rotation and scaling as translations in parameter space. The matching of the FMI descriptors is achieved using symmetric phase-only matched filtering (SPOMF). The performance of the FMI-SPOMF algorithm is the same or similar to that of phase-only matched filtering when dealing with image translations. The significant advantage of the new technique is its capability to match rotated and scaled images accurately and efficiently. The innovation is the application of SPOMF to the FMI descriptors, which guarantees high discriminating power and excellent robustness in the presence of noise. This paper describes the principle of the new method and its discrete implementation for either image detection problems or image registration problems. Practical results are presented for various applications in medical imaging, remote sensing, fingerprint recognition and multiobject identification. >

Symmetric phase-only matched filtering of Fourier-Mellin transforms for image registration and recognition

A new method has been developed for rotation-invariant pattern recognition. One component of the circular harmonic expansion of the target is used in the preparation of the reference. Correlations between the input and reference objects are accomplished by FFT and multiplication in the frequency domain. In an experience with targets from an image with 192 × 192 pixels, target orientations were detected with an accuracy of ~0.1°. This method is also suitable for optical implementation.

Rotation-invariant digital pattern recognition using circular harmonic expansion.

When image plane speckle intensity integrated over a finite aperture is submitted to a logarithmic transformation, the noise becomes additive and signal independent. The first- and second-order moments of the probability distribution are derived. It is found that the logarithm of speckle noise approaches a normal distribution much faster than speckle intensity. The properties of speckle noise are different from those of film-grain noise; for example, neither Nutting’s law nor Selwyn’s law is satisfied by speckle.

Properties of speckle integrated with a finite aperture and logarithmically transformed

Speckle noise in high-resolution synthetic aperture radar (SAR) images is generated by the coherent processing of radar signals and exists in all types of coherent imaging systems. We study the statistical properties of speckle noise in a four-look SEASAT SAR image concentrating on homogeneous areas of the image. Experimental determination of the signal-to-noise ratio and ofthe probability density of the recorded intensity is performed showing evidence of correlation between underlying looks. Based on a model taking into account the weighting and possible correlation between the underlying looks, a theoretical expression for the effective number of independent looks is proposed and the corresponding probability density function of the intensity is compared to the experimentally extracted histograms of intensity fluctuations.

Speckle statistics in four-look synthetic aperture radar imagery

After a homomorphic transformation has been used to transform speckle noise into additive signal-independent noise, classic techniques are used to evaluate the number of discernible gray levels and the information capacity of images degraded by fully developed speckle noise. The probability distributions that we developed earlier are used to evaluate the required probabilities of error. Expressions are derived for square and for circular apertures. The information capacity is found to have a maximum of about 0.2 bits per speckle. The spatial frequency resolution required to obtain a given signal-to-noise ratio by spatial integration is evaluated.

Information content of images degraded by speckle noise

The performance of computer-generated holographic matched filters recorded on 128 x 128 pixel supports was studied experimentally, with the objective of recording holograms on spatial light modulators such as the Semetex SIGHT-MOD for rotation-invariant pattern recognition. A new method of diagonal coding is introduced. This method yields good results, as it allows a more accurate phase quantization. Experimental results from computer simulations show that high speed rotation-invariant recognition of simple shapes is possible with such holograms.

Gilbert V. April

Papers

Rotation-invariant digital pattern recognition using circular harmonic expansion.

Properties of speckle integrated with a finite aperture and logarithmically transformed

Speckle statistics in four-look synthetic aperture radar imagery

Information content of images degraded by speckle noise

Recording holograms with diagonal coding on binary spatial light modulators for pattern recognition