This book presents today's most powerful signal processing techniques together with methods for assessing imaging system performance when each of these techniques is applied. This multi-use book helps you make the most of sensor hardware through software enhancement, and evaluate system and algorithm performance. You also learn how to make the best hardware/software decisions in developing the next-generation of image acquisition and analysis systems.

This rigourous and self-contained book describes mathematical and, in particular, stochastic methods to assess the performance of networked systems. It consists of three parts. The first part is a review on probability theory. Part two covers the classical theory of stochastic processes (Poisson, renewal, Markov and queuing theory), which are considered to be the basic building blocks for performance evaluation studies. Part three focuses on the relatively new field of the physics of networks. This part deals with the recently obtained insights that many very different large complex networks - such as the Internet, World Wide Web, proteins, utility infrastructures, social networks - evolve and behave according to more general common scaling laws. This understanding is useful when assessing the end-to-end quality of communications services, for example, in Internet telephony, real-time video and interacting games. Containing problems and solutions, this book is ideal for graduate students taking courses in performance analysis.

Image enhancement is an important procedure of image processing and analysis as one of the most important techniques in image research. The key objective of image enhancement is to boost the quality and visual manifestation of an image, or to furnish a better transform depiction for future automated image processing. Many images like medical images, satellite, aerial images and also real life photographs suffer from poor and bad contrast and noise. It is crucial to augment the contrast and remove the noise to increase image quality. One of the most significant stages in medical images detection and analysis is Image Enhancement Techniques. It advances the clarity of images for human viewing, removing blurring and noise, escalating contrast, and illuminating details. Signal Processing and Performance Analysis for Imaging Systems covers theoretical, experimental and applied aspects of the engineering design of signal and imaging systems, with emphasis on signal generation and image formation mechanisms, transmission, sensing, analysis and processing, and post-processing algorithms. It provides State-of-the-art systems analysis; design, integration, evaluation, standardization, and the development of algorithms evaluated towards building such systems are the journal's primary focus. The visual quality of the most recorded images is often brought down in the course of digital image acquisition because of some factors such as uneven illumination, the noise produced in the transmission, and D/A transformation. As a consequence, image quality usually needs to be improved before image analysis; image enhancement is an elementary step in digital image processing and analysis. The book enables specialists get the most out of current imaging systems and make the best hardware/software decisions in budding the next-generation image acquisition and analysis competence their work needs. Practitioners will discover today's most advanced techniques for single image reconstruction, super-resolution image reconstruction, image deblur and restoration, and contrast enhancement.

Academic Press Library in Signal Processing, Volume 6: Image and Video Processing and Analysis and Computer Vision is aimed at university researchers, post graduate students and R&D engineers in the industry, providing a tutorial-based, comprehensive review of key topics and technologies of research in both image and video processing and analysis and computer vision. The book provides an invaluable starting point to the area through the insight and understanding that it provides. With this reference, readers will quickly grasp an unfamiliar area of research, understand the underlying principles of a topic, learn how a topic relates to other areas, and learn of research issues yet to be resolved. - Presents a quick tutorial of reviews of important and emerging topics of research - Explores core principles, technologies, algorithms and applications - Edited and contributed by international leading figures in the field - Includes comprehensive references to journal articles and other literature upon which to build further, more detailed knowledge

If you understand basic mathematics and know how to program with Python, you’re ready to dive into signal processing. While most resources start with theory to teach this complex subject, this practical book introduces techniques by showing you how they’re applied in the real world. In the first chapter alone, you’ll be able to decompose a sound into its harmonics, modify the harmonics, and generate new sounds. Author Allen Downey explains techniques such as spectral decomposition, filtering, convolution, and the Fast Fourier Transform. This book also provides exercises and code examples to help you understand the material. You’ll explore: Periodic signals and their spectrums Harmonic structure of simple waveforms Chirps and other sounds whose spectrum changes over time Noise signals and natural sources of noise The autocorrelation function for estimating pitch The discrete cosine transform (DCT) for compression The Fast Fourier Transform for spectral analysis Relating operations in time to filters in the frequency domain Linear time-invariant (LTI) system theory Amplitude modulation (AM) used in radio Other books in this series include Think Stats and Think Bayes, also by Allen Downey.

With the proliferation of digital audio distribution over digital media, audio content analysis is fast becoming a requirement for designers of intelligent signal-adaptive audio processing systems. Written by a well-known expert in the field, this book provides quick access to different analysis algorithms and allows comparison between different approaches to the same task, making it useful for newcomers to audio signal processing and industry experts alike. A review of relevant fundamentals in audio signal processing, psychoacoustics, and music theory, as well as downloadable MATLAB files are also included. Please visit the companion website: www.AudioContentAnalysis.org

Presents state-of-the-art sparse and multiscale image and signal processing with applications in astronomy, biology, MRI, media, and forensics.