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This lecture covers the concept of images with more than two dimensions, discussing the width, height, and channels of such images. It explains the relationship between image size and dimensions, illustrating examples with different sizes and corresponding memory requirements. The lecture also addresses processing time in relation to image size, highlighting the trade-offs and compromises that need to be considered. Additionally, it touches upon the challenges of dealing with multi-dimensional images, such as spatial and temporal resolutions, noise, and the impact on data processing.