'Periodic noise' presentation slideshows

Limitation of Imaging Technology

Limitation of Imaging Technology. Two plagues in image acquisition Noise interference Blur (motion, out-of-focus, hazy weather) Difficult to obtain high-quality images as imaging goes Beyond visible spectrum Micro-scale (microscopic imaging) Macro-scale (astronomical imaging).

1.19k views • 54 slides

Computer Vision - Restoration

Computer Vision - Restoration. Hanyang University Jong-Il Park. Restoration vs. Enhancement. To improve an image in some predefined sense. Restoration. Enhancement. Objective process A priori knowledge on degradation model Modeling the degradation and applying the inverse process

596 views • 53 slides

Chapter 5

Chapter 5. Image Restoration. Preview. Goal: improve an image in some predefined sense. Image enhancement: subjective process Image restoration: objective process Restoration attempts to reconstruct an image that has been degraded by using a priori knowledge of the degradation process.

708 views • 48 slides

Chapter 5

Chapter 5. Image Restoration. Preview. Goal: improve an image in some predefined sense. Image enhancement: subjective process Image restoration: objective process Restoration attempts to reconstruct an image that has been degraded by using a priori knowledge of the degradation process.

504 views • 48 slides

Chapter 5

Chapter 5. Image Restoration. Preview. Goal: improve an image in some predefined sense. Image enhancement: subjective process Image restoration: objective process Restoration attempts to reconstruct an image that has been degraded by using a priori knowledge of the degradation process.

488 views • 48 slides

Digital Image Processing

Digital Image Processing. Image Restoration: Noise Removal. Contents. In this lecture we will look at image restoration techniques used for noise removal What is image restoration? Noise and images Noise models Noise removal using spatial domain filtering Periodic noise

469 views • 44 slides

Digital Image Processing

Digital Image Processing. Image Restoration: Noise Removal. Contents. In this lecture we will look at image restoration techniques used for noise removal What is image restoration? Noise and images Noise models Noise removal using spatial domain filtering Periodic noise

456 views • 44 slides

ECE 472/572 - Digital Image Processing

ECE 472/572 - Digital Image Processing. Lecture 7 - Image Restoration - Noise Models 10/04/11. Image Acquisition. Image Enhancement. Image Segmentation. Image Restoration. Representation & Description. Image Compression. Recognition & Interpretation. Image Coding. Morphological

722 views • 40 slides

Image Restoration - Focus on Noise

Image Restoration - Focus on Noise. References. Gonzales and Wood second edition Jain. Enhancement - Restoration. Overview. Measured. From [1]. Unknown Approximation. Noise sources. Device noise (often thermal) Digitization process Sampling and quantization Transmission Environment.

364 views • 27 slides

Noise and Filtering

Basis beeldverwerking ( 8D040) d r. Andrea Fuster Prof.dr . Bart ter Haar Romeny dr. Anna Vilanova Prof.dr . Marcel Breeuwer. Noise and Filtering. Contents. Noise Mean Filters Order-statistic filters Median Alpha-trimmed. Gaussian Noise.

435 views • 25 slides

Image Analysis

Image Analysis. Image Restoration. Image Restoration. Image enhancement tries to improve subjective image quality. Image restoration tries to recover the original image. Noise Models. Noise may arise during image due to sensors, digitization, transmission, etc.

541 views • 25 slides

From microseismic event to reservoir characterisation: A workflow

381 views • 18 slides

Image Processing

Image Processing. Image Restoration Part III. Adaptive Filters. The filters discussed so far are applied to an entire image without any regard for how image characteristics vary from one point to another

514 views • 14 slides