Reconstructing Color Images: Techniques and Applications

This lecture discusses the methods for reconstructing color images using optical detection techniques. It begins with an overview of color filters, specifically the standard configuration of four filters: two green, one blue, and one red. The instructor emphasizes the importance of reading relevant literature to understand improvements in color filtering and image reconstruction. The lecture explains how to fit the red color value at a pixel based on neighboring pixels to enhance color information. A key focus is on controlled displacement, where multiple images are taken by shifting the sensor slightly to fill in unknown pixel values. The challenge of alignment is highlighted, particularly when hand tremors cause movement. The instructor presents a solution that utilizes hand tremors as a controlled movement, employing artificial intelligence to align images and reduce noise. This approach allows for effective edge detection and alignment of stable objects, showcasing a positive application of hand tremors in image processing.