A review and tutorial of the fundamental ideas and methods of joint time-frequency distributions is presented. The objective of the field is to describe how the spectral content of a signal changes in time and to develop the physical and mathematical ideas needed to understand what a time-varying spectrum is. The basic gal is to devise a distribution that represents the energy or intensity of a signal simultaneously in time and frequency. Although the basic notions have been developing steadily over the last 40 years, there have recently been significant advances. This review is intended to be understandable to the nonspecialist with emphasis on the diversity of concepts and motivations that have gone into the formation of the field. >

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Time-frequency distributions-a review

A general framework for multiresolution image fusion: from pixels to regions

A general framework based on histogram equalization for image contrast enhancement is presented. In this framework, contrast enhancement is posed as an optimization problem that minimizes a cost function. Histogram equalization is an effective technique for contrast enhancement. However, a conventional histogram equalization (HE) usually results in excessive contrast enhancement, which in turn gives the processed image an unnatural look and creates visual artifacts. By introducing specifically designed penalty terms, the level of contrast enhancement can be adjusted; noise robustness, white/black stretching and mean-brightness preservation may easily be incorporated into the optimization. Analytic solutions for some of the important criteria are presented. Finally, a low-complexity algorithm for contrast enhancement is presented, and its performance is demonstrated against a recently proposed method.

A Histogram Modification Framework and Its Application for Image Contrast Enhancement

The objective of image fusion is to combine information from multiple images of the same scene. The result of image fusion is a single image which is more suitable for human and machine perception or further image-processing tasks. In this paper, a generic image fusion framework based on multiscale decomposition is studied. This framework provides freedom to choose different multiscale decomposition methods and different fusion rules. The framework includes all of the existing multiscale-decomposition-based fusion approaches we found in the literature which did not assume a statistical model for the source images. Different image fusion approaches are investigated based on this framework. Some evaluation measures are suggested and applied to compare the performance of these fusion schemes for a digital camera application. The comparisons indicate that our framework includes some new approaches which outperform the existing approaches for the cases we consider.

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A categorization of multiscale-decomposition-based image fusion schemes with a performance study for a digital camera application

The history and fundamentals of distributed arithmetic (DA) are presented. Ways to increase the speed of DA multiplication are described. DA is applied to a biquadratic digital filter, providing an example of vector dot-product and vector-matrix-product mechanization. Applications to transformers and nonlinear and/or nonstationary processing with DA are discussed. It is seen that DA is a very efficient means to mechanize computations that are dominated by inner products. >

Applications of distributed arithmetic to digital signal processing: a tutorial review

Chapter 1: Introduction to Modern Network Theory Chapter 2: Selecting the Response Characteristic Chapter 3: Low-Pass Filter Design Chapter 4: High-Pass Filter Design Chapter 5: Bandpass Filters Chapter 6: Band-Reject Filters Chapter 7: Networks for the Time Domain Chapter 8: Refinements in LC Filter Design and the Use of Resistive Networks Chapter 9: Design and Selection of Inductors for LC Filters Chapter 10: Component Selection for LC and Active Filters Chapter 11: Normalized Filter Design Tables Chapter 12: Introduction to Digital Filters Chapter 13: Finite Impulse-Response Filters Chapter 14: Infinite Impulse-Response Filters Chapter 15: Multirate Digital Filters Chapter 16: Digital Filter Technology Chapter 17: Switched-Capacitor Filters Chapter 18: Introduction to Microwave Filters APPENDIX A: DISCRETE SYSTEMS MATHEMATICS APPENDIX B: SOFTWARE SUMMARY INDEX

Electronic filter design handbook

Digital Filter Design Handbook

An image fusion algorithm based on multiscale analysis along arbitrary orientations is presented. After a steerable dyadic wavelet transform decomposition of multi-sensor images is carried out, the maximum local oriented energy is determined at each level of scale and spatial position. Maximum local oriented energy and local dominant orientation are used to combine transform coefficients obtained from the analysis of each input image. Reconstruction is accomplished from the modified coefficients, resulting in a fused image. Examples of multi-sensor fusion and fusion using different settings of a single sensor are demonstrated.

/pdf/image-fusion-using-steerable-dyadic-wavelet-transform-4ctbzyf0it.pdf

Image fusion using steerable dyadic wavelet transform

Discrete-Time Signals and Systems Frequency-Domain Signal and System Analysis The Discrete Fourier Transform Digital Filter Design Stochastic Processes State Variable Analysis Multirate Signal Processing Wiener Filtering Adaptive Filtering: Gradient Descent Algorithms Adaptive Filtering: Recursive Least Squares Power Spectrum Estimation Appendix: Mathematical Review References

Advanced Digital Signal Processing: Theory and Applications

Field-programmable logic (FPL), often grouped under the popular name field-programmable gate arrays (FPGA), are on the verge of revolutionizing sectors of digital signal processing (DSP) industry as programmable DSP microprocessor did nearly two decades ago. Historically, FPGAs were considered to be only a rapid prototyping and low-volume production technology. FPGAs are now attempting to move into the mainstream DSP as their density and performance envelope steadily improve. While evidence now supports the claim that FPGAs can accelerate selected low-end DSP applications (e.g., FIR filter), the technology remains limited in its ability to realize high-end DSP solutions. This is due primarily to systemic weaknesses in FPGA-facilitated arithmetic processing. It will be shown that in such cases, the residue number system (RNS) can become an enabling technology for realizing embedded high-end FPGA-centric DSP solutions. This thesis is developed in the context of a demonstrated RNS/FPGA synergy and the application of the new technology to communication signal processing.

Fred J. Taylor

Papers

Electronic filter design handbook

Digital Filter Design Handbook

Image fusion using steerable dyadic wavelet transform

Advanced Digital Signal Processing: Theory and Applications

Implementation of a Communications Channelizer using FPGAs and RNS Arithmetic