Digital Image Processing Quiz

The given correct answer is "dark". In a dark image, the components of the histogram are concentrated on the low side of the intensity scale. This means that the majority of the pixels in the image have low intensity values, resulting in a darker overall appearance.

Two different images may have the same histograms because histograms only represent the frequency distribution of pixel intensities in an image. It does not provide any information about the actual content or appearance of the image. Therefore, it is possible for two different images to have the same distribution of pixel intensities and consequently the same histogram.

The correct answer is Median Filter. The Median Filter is used to remove "salt-and-pepper" noise without blurring the image. It replaces each pixel value with the median value of its neighboring pixels. This filter is effective in removing isolated noise pixels while preserving the edges and details in the image.

Sharpening is a technique used to enhance the clarity and detail of an image. In the context of a Nuclear Whole Body Bone Scan, sharpening can be used to bring out more of the skeletal detail, making it easier to identify any abnormalities or issues. By applying sharpening algorithms or filters, the image can be enhanced to highlight the bones and their structure, providing a clearer and more detailed view.

Edge detection in images is commonly accomplished by performing a spatial sharpening filter on the image field. This filter enhances the high-frequency components in the image, making the edges more pronounced. By increasing the contrast between adjacent pixels, the sharpening filter helps to identify and highlight the edges present in the image. This is why the sharpening filter is a commonly used technique for edge detection in image processing.

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In the sharpening spatial filtering (Laplacian), the sum of all elements in the mask must be equal to 0. This is because the Laplacian filter is designed to enhance the high-frequency components in an image, which are represented by the edges and details. By setting the sum of the mask elements to 0, the filter ensures that the overall intensity of the image is preserved while emphasizing the edges and details.

In global histogram processing, the modification of pixels is based on the intensity distribution of the entire image. This means that the adjustments are applied uniformly to all pixels in the image, regardless of their location or context. Global histogram processing is commonly used to enhance contrast, brightness, or overall appearance of an image. It is a widely used technique in image processing and allows for global adjustments to be made to the entire image at once.

The given answer, 24 31, is the median value of the marked pixels in the figure. To find the median, we arrange the marked pixels in ascending order: 24, 24, 25, 26, 31, 34. Since there are 6 pixels, the median is the average of the 3rd and 4th values, which are 25 and 26. Therefore, the median value is 24 31.

When the pixels of an image are shuffled, the arrangement of the pixels changes but the actual values of the pixels remain the same. This means that the histogram, mean, median, and mode of the image will all stay the same. Therefore, none of these parameters will change when the pixels of an image are shuffled.