In this paper, a novel approach to the impulsive noise removal in color images is presented. The proposed technique employs the switching scheme based on the impulse detection mechanism using the so-called peer group concept. Compared to the vector median filter and other commonly used multichannel filters, the proposed technique consistently yields very good results in suppressing both the random and fixed-valued impulsive noise. The main advantage of the proposed noise detection framework is its enormous computational speed, which enables efficient filtering of color images in real-time applications.

Fast detection and impulsive noise removal in color images

The image coding method is used to code images to generate a coded stream. The image coding method includes: writing, into a sequence parameter set in the coded stream to be generated, a first parameter representing a first bit-depth that is a bit-depth of a reconstructed sample in the images; and writing, into the sequence parameter set, a second parameter which is different from the first parameter and represents a second bit-depth that is a bit-depth of an Intra Pulse Code Modulation (IPCM) sample in the images.

Image coding method, image decoding method, image coding apparatus, image decoding apparatus, and image coding and decoding apparatus

This new textbook by R. E. Blahut, which deals with the theory and design of efficient algorithms for digital signal processing, contains perhaps the most comprehensive coverage of fast algorithms todate.Alargecollectionofalgorithmsistreated,withanemphasis on implementing the two canonical signal processing operations of convolution and discrete Fourier transformation. In recent years, there has been much work done on fast algorithms,andBlahutdoesafinejobofblendingmaterialfromdiverse sources to form a coherent and self-contained approach to his subject.The mathematical level of this book is high, reflecting the rather abstract nature of the theoretical underpinnings of fast computational techniques. Although electrical engineers are forthe most part mathematically sophisticated, they tend to lack training in abstract algebra and number theory, both of which are essential to any thorough discussion of fast algorithms. Thus this audience should find the tutorial chapters which the text provides on these topics to be quite helpful. An additional feature of the text, which the nonspecialist should find useful, is that each new algorithm is described through three different formats: a simple example, a flowchart, and a set of matrix equations. This use of repetition assists the reader in grasping subject matter which for the most part is nonintuitive. Operation counts (as measured by the number of multiplications and the number of additions) for each algorithm are tabulated for avarietyof blocklengths (i.e., lengths of data segments), making performance comparisons easy. As the author points out, run-time comparisons may be quite different. Each chapter concludes with a set of problems of varying difficulty. These problems are well integrated with the text and serve to supplement the many examples worked out in the text. The book is devoted to how one rapidly computes various mathematical operators such as transform and convolutions. For a deeper understanding of the meaning of theseoperators,one must consult other sources in which their use is discussed. The text emphasizes algorithms which employ a reduced, or minimum, numberof muItiplications,althoughadditioncountsarealsotaken into consideration. However, an algorithm which is the “fastest” as measured in arithmetic operation counts may not be the fastest in execution time, particularly if dedicated hardware is employed. Indeed in practiceother considerationsfrequentlypropel oneaway from the computationally ”optimal” algorithm. Much work has been done on the theory and application of signal processing algorithms which are “efficient” in terms other than rnultiply/add counts, such as roundoff noise, limit cycles, coefficient quantization, memory access, hardware costs, etc. It is clearly necessary to limit the scope of any treatise, and the exclusion of differing performance measures is certainly appropriate. A description of the contents of the book will now be given, followed by some concluding remarks of a more general nature. Chapter 2 i s a tutorial on abstract algebra. It i s quite readable and is liberally laced with examples. In addition to the standard modern algebra fare (groups, rings, fields, vector spaces, matrices), the ubiquitous Chinese remainder theorem is discussed in detail. Chapters 3 and 4, and their extensions in Chapters 7and 8, form the core of the text. The third chapter addresses fast algorithms for short convolutions. The Cook-Toom convolution algorithm is discussed, followed by the Winograd convolution algorithm. A proof of the optimality of the Winograd algorithm, with respect to multiplications, for performing cyclic convolutions, is presented at the close of the chapter. The fourth chapter addresses fast algorithms for computing the discrete Fourier transform. The CooleyTukey algorithm is considered first. The approach taken is to view this algorithm as a means of mapping a onedimensional Fourier transform into a multidimensional transform. Variations of the algorithm are discussed, including the Rader-Brenner transform. Next, the Good-Thomas algorithm is discussed. This algorithm is again presented as a means of mapping a onedimensional transform into a higher dimensional transform, this time based on the Chinese remainder theorem. Rader’s algorithm for computing primelength Fouriertransforms by useofconvolution ispresented next. Extensions of the algorithm to blocklengths which are the power of an odd prime are considered. The chapter closes with the Winograd-Fourier transform which builds upon the Rader prime algorithm. Certain short blocklengthsareconsidered in detail,and the corresponding algorithms are compiled into an Appendix. Chapter 5 i s a mathematical interlude, tutorially covering items from number theory and algebraic field theory which are needed in later chapters. Topics include the totient function, Euler’s theorem,  Fermat’s theorem, minimal polynomials, and cyclotomic polynomials. Chapter 6 is devoted to number theoretic transforms. These transforms proceed by representing the data values themselves in the field of integers modulo a prime. Convolution in integer fields is also covered. Chapters 7and 8 extend the convolution and transform methods of Chapters 3 and 4 to higher dimensions. Multidimensional transforms (convolutions) are used both to efficiently compute onedimensional transforms (convolutions) and to process data which are inherently higher dimensional. Both applications are treated in these chapters. Topics include the Agarwal-Cooley convolution algorithm, polynomial transforms, the family of Johnson-Burrus transforms and the Nussbaumer-Quandalle FFT. Chapter 9 discusses architectures for transforms and digital filters and includes treatmentsof FFT butterfly networks and overlapadd convolution. The remaining three chapters are mostly independent from the rest of the book. Chapter 10 covers fast algorithms based on doubling strategies. Computational tasks for which such fast algorithms are derived include sorting, matrix transposition, matrix multiplication, polynomial division, computation of trigonometric functions, and coordinate rotation. Many of theseoperations arise as steps in the solution of oneor more signal processing problems. Fast algorithms for solving Toeplitz systems is the theme of Chapter 11. There is a variety of fast algorithms discussed, the proper choice of which depends on the specific structure of the Toeplitz system at hand (such as whether or not the system is symmetric and whether or not the right-hand vector is arbitrary). The final chapter addresses fast algorithms for Trellis and tree search and includes the Viterbi, Stack, and Fano algorithms. These

Fast algorithms for digital signal processing

An electronic device coupleable to a display screen includes a camera system that acquires optical data of a user comfortably gesturing in a user-customizable interaction zone having a z 0 plane, while controlling operation of the device. Subtle gestures include hand movements commenced in a dynamically resizable and relocatable interaction zone. Preferably (x,y,z) locations in the interaction zone are mapped to two-dimensional display screen locations. Detected user hand movements can signal the device that an interaction is occurring in gesture mode. Device response includes presenting GUI on the display screen, creating user feedback including haptic feedback. User three-dimensional interaction can manipulate displayed virtual objects, including releasing such objects. User hand gesture trajectory clues enable the device to anticipate probable user intent and to appropriately update display screen renderings.

Method and system enabling natural user interface gestures with an electronic system

A Taxonomy of Color Image Filtering and Enhancement Solutions

A robust structure-adaptive hybrid vector filter is proposed for digital color image restoration in this paper. At each pixel location, the image vector (i.e., pixel) is first classified into several different signal activity categories by applying a modified quadtree decomposition to luminance component (image) of the input color image. A weight-adaptive vector filtering operation with an optimal window is then activated to achieve the best tradeoff between noise suppression and detail preservation. Through extensive simulation experiments conducted using a wide range of test color images, the filter has demonstrated superior performance to that of a number of well known benchmark techniques, in terms of both standard objective measurements and perceived image quality, in suppressing several distinct types of noise commonly considered in color image restoration, including Gaussian noise, impulse noise, and mixed noise.

A robust structure-adaptive hybrid vector filter for color image restoration

A partition-based adaptive vector filter is proposed for the restoration of corrupted digital color images. The novelty of the filter lies in its unique three-stage adaptive estimation. The local image structure is first estimated by a series of center-weighted reference filters. Then the distances between the observed central pixel and estimated references are utilized to classify the local inputs into one of preset structure partition cells. Finally, a weighted filtering operation, indexed by the partition cell, is applied to the estimated references in order to restore the central pixel value. The weighted filtering operation is optimized off-line for each partition cell to achieve the best tradeoff between noise suppression and structure preservation. Recursive filtering operation and recursive weight training are also investigated to further boost the restoration performance. The proposed filter has demonstrated satisfactory results in suppressing many distinct types of noise in natural color images. Noticeable performance gains are demonstrated over other prior-art methods in terms of standard objective measurements, the visual image quality and the computational complexity.

/pdf/partition-based-vector-filtering-technique-for-suppression-1igukdy96k.pdf

Partition-based vector filtering technique for suppression of noise in digital color images

Methods, apparatuses ( 100, 400, 1000 ), and computer program products for generating an enhanced digital image ( 490, 495, 1022 ) comprising a plurality of pixels are disclosed. Using a first digital image ( 420, 1020 ) captured from a first camera ( 124 ) and parity bits ( 410, 415, 1010 ) generated from a second digital image captured by a second camera ( 122, 126 ), a third digital image ( 445, 447, 1045 ) is constructed. The second camera ( 122, 126 ) captures the second image at a resolution different to the resolution of the first camera ( 124 ) capturing the first image ( 420, 1020 ). A disparity map ( 455, 457, 1055 ) between the first image ( 420, 1020 ) and the third image ( 445, 447, 1045 ) is determined ( 450, 452, 1050 ). One of the first image ( 420, 1020 ) and the third image ( 445, 447, 1045 ) is enhanced ( 470, 472, 1070 ) dependent upon the determined disparity map ( 455, 457, 1055 ) to generate the enhanced digital image ( 490, 495, 1022 ).

Processing multi-view digital images

Infrared imaging is a crucial technique in a multitude of applications, including night vision, autonomous vehicle navigation, optical tomography, and food quality control. Conventional infrared imaging technologies, however, require the use of materials such as narrow bandgap semiconductors, which are sensitive to thermal noise and often require cryogenic cooling. We demonstrate a compact all-optical alternative to perform infrared imaging in a metasurface composed of GaAs semiconductor nanoantennas, using a nonlinear wave-mixing process. We experimentally show the upconversion of short-wave infrared wavelengths via the coherent parametric process of sum-frequency generation. In this process, an infrared image of a target is mixed inside the metasurface with a strong pump beam, translating the image from the infrared to the visible in a nanoscale ultrathin imaging device. Our results open up new opportunities for the development of compact infrared imaging devices with applications in infrared vision and life sciences.

/pdf/infrared-upconversion-imaging-in-nonlinear-metasurfaces-2fik0gs6zq.pdf

Infrared upconversion imaging in nonlinear metasurfaces

A new adaptive vector filter is proposed for impulse noise suppression and its relationship with the recent impulse reduction filters is investigated. The new filter detects outliers presented in the image through a novel neighborhood evaluation process, which significantly improves the accuracy of noise detection and detail preservation. The computational complexity of the new filter is very competitive. Its two parameters can be configured efficiently using online/offline optimization processes. Extensive simulations indicated that the new filter outperforms other prior-art methods in suppressing impulse noise in natural color images.

Zhonghua Ma

Papers

A robust structure-adaptive hybrid vector filter for color image restoration

Partition-based vector filtering technique for suppression of noise in digital color images

Processing multi-view digital images

Infrared upconversion imaging in nonlinear metasurfaces

A neighborhood evaluated adaptive vector filter for suppression of impulse noise in color images