Image Enhancement & Noise Suppression for Students
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62 cards
Question: What are the primary aims of image enhancement?
Answer: Improvement of subjective impression, facilitating image analysis, more efficient use of information, and increasing diagnostic yield.
Question: What does image enhancement NOT accomplish?
Answer: It does not increase the inherent quality of the image, create new information, or restore the original image.
Question: Give a concise definition of image enhancement.
Answer: Selective enhancement of some image features at the expense of others to improve subjective impression and information use.
Question: Name common categories of contrast enhancement techniques listed.
Answer: Brightness and contrast transforms, false and pseudo-coloring, histogram equalization, and white correction.
Question: What is contrast resolution and what does it depend on?
Answer: Contrast resolution is the minimum distance of adjacent quantization levels and depends on intensity range and bit depth.
Question: How is overall image contrast commonly quantified in the slides?
Answer: By RMS (root mean square) of intensities and by Michelson contrast (Imax−Imin)/(Imax+Imin).
Question: What is the trade-off inherent in contrast enhancement methods?
Answer: They increase contrast in a specific intensity range at the expense of other ranges and do not add new information.
Question: What form do most contrast enhancement operators take?
Answer: Point-wise nonlinear isoplanar operators, often implemented via a transformation function or look-up table.
Question: Write the basic linear transformations used for brightness and contrast in images.
Answer: Additive brightness: g = f + b; Multiplicative contrast: g = f · k; Combined linear: g = f · k + b.
Question: How are linear transformations implemented in discrete images?
Answer: By using a Look-Up-Table mapping each input gray level to an output gray level.