What is it about?
This book is intended for those interested in the boundary between sensor systems and analog and mixed-signal integrated circuit design. It provides in-depth tips and techniques necessary to understand these two types of complex circuit systems together over wide variety of architectures or trade off one architecture against another. The tutorial begins with a brief introduction to the history and definition of a digital image sensor, as well as converter characteristics, before addressing converter architectures. Later chapters cover pipeline ADC designs, digital correction, calibration, and testing according to IEEE standards.
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Why is it important?
This book could save an image system designer time, effort and electrical resources by explaining the key differences in how image sensing systems and digital converters are specified. In some cases a designer might be able to cut out more than half the power consumption of their conversion system by realizing that converters may possibly be have 9 dB better SNR than what they might expect when considering image sensor SNR specifications. This book also provides a very digestible overview of architectures and test strategies which will help quickly solidify trade studies and designs.
Perspectives
I have enjoyed the boundary between real-world analog phenomena and the computational world of binary numbers and symbols every since I took a course on the subject from Professor Franco Maloberti at Texas A&M University. I have found some of the most interesting circuitry sometimes has the most constraints, as is the case with converters for image sensors where thousands or even millions of converters must work in harmony on the same piece of silicon to produce the amazing photographs we all take for granted. My inspiration for this book was to try and explain how this is done for readers who may not have the need or desire to dive down deep into the world of solid-state circuits.
Mr Kenton Veeder
Read the Original
This page is a summary of: Digital Converters for Image Sensors, January 2015, SPIE,
DOI: 10.1117/3.1000639.
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