Image Processing I: Quantization and Histogram Analysis

Related lectures (31)

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Explores distributed algorithms for networked control systems, covering consensus, least-squares regression, and time-varying communication networks.

Explores quantization and coding of digital signals, discussing uniform quantization, error analysis, and signal-to-quantization noise ratio.

Explores digital design principles, ADC architectures, FPGA-based ADCs, figures of merit, and lower bounds in digital design.

Covers the concept of the Wigner function in quantum optics.

Explores noise reduction techniques in electrical systems, covering concepts like Fourier transform, impedance matching, and dithering.

Explains ADC operation, quantization, encoding, and different architectures, covering ENOB, SNDR, and ADC comparison.

Covers advanced topics in Quantum Field Theory, including quantization of fields and the organization of fields into irreducible representations.

Explains uniform quantization in signal processing and how quantization noise increases with each additional bit.

Explores imaging cameras' characteristics, spatial resolution, noise sources, and dynamic range for optimal performance in microscopy applications.

Explores analog-digital conversion principles, quantization, and converter implementations, emphasizing speed, precision, and energy efficiency.