Computer Knowledge
Digital Image Processing
2,103 Questions
Digital image processing involves manipulating digital images through various algorithms to enhance their visual quality or extract information. Key concepts include noise reduction, high dynamic range imaging, color correction, and sharpening techniques. These concepts are essential for computer science exams and technical certifications.
Color management systemsNoise reduction techniquesHDR image combiningImage sharpening techniquesAlpha matting process
Digital Image Processing Questions
Which of the following is NOT a common HDR photography post-processing technique for reducing noise?
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Median filter
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Gaussian blur
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Denoise algorithm
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HDR merging
D
Correct answer
Explanation
HDR merging is a technique for combining multiple exposures into a single HDR image, not for reducing noise.
Which of the following is NOT a common HDR photography post-processing technique for improving image sharpness?
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Unsharp mask
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High-pass filter
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Median filter
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Gaussian blur
C
Correct answer
Explanation
Median filter is a noise reduction technique, not a sharpening technique.
Which of the following is NOT a common HDR photography post-processing technique for creating a more artistic and stylized image?
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HDR toning
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Color grading
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Vignette
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Noise reduction
D
Correct answer
Explanation
Noise reduction is not a technique for creating a more artistic and stylized image, but rather for improving image quality.
Which of the following is NOT a common HDR photography post-processing technique for merging multiple exposures?
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Exposure blending
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HDR merging
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Focus stacking
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Tone mapping
C
Correct answer
Explanation
Focus stacking is a technique for combining multiple images with different focus points to create a single image with extended depth of field. It is not commonly used for merging multiple exposures in HDR photography.
Which of the following is NOT a common HDR photography post-processing technique for reducing halos and artifacts?
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Tone mapping
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Exposure blending
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Local contrast adjustment
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HDR merging
D
Correct answer
Explanation
HDR merging is a technique for combining multiple exposures into a single HDR image, not for reducing halos and artifacts.
Which of the following is NOT a type of texture?
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Diffuse texture
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Normal map
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Specular map
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Displacement map
D
Correct answer
Explanation
Displacement maps are not a type of texture. They are a type of geometry map that can be used to add detail to a surface.
How can white balance be adjusted in post-processing?
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Using a color correction filter
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Adjusting the color temperature
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Using a white balance dropper tool
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All of the above
D
Correct answer
Explanation
White balance can be adjusted in post-processing using a variety of methods. One common method is to use a color correction filter. This filter can be applied to the entire image or to specific areas of the image. Another method is to adjust the color temperature. This can be done using a slider or by entering a specific value in degrees Kelvin. Finally, a white balance dropper tool can be used to select a neutral gray area in the image and set the white balance accordingly.
Which sharpening method is commonly used for street photography?
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Unsharp Mask
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High Pass Filter
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Median Filter
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Gaussian Blur
A
Correct answer
Explanation
Unsharp Mask is a popular sharpening method used in street photography due to its ability to enhance the sharpness of the image while preserving the overall detail.
What is the primary adjustment made in the Unsharp Mask sharpening method?
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Amount
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Radius
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Threshold
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All of the above
D
Correct answer
Explanation
In the Unsharp Mask sharpening method, adjustments are made to the Amount, Radius, and Threshold to control the intensity, spread, and sensitivity of the sharpening effect.
What is the function of the Radius parameter in the Unsharp Mask sharpening method?
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It determines the size of the sharpening radius
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It controls the strength of the sharpening effect
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It sets the threshold for detecting edges
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It adjusts the contrast of the image
A
Correct answer
Explanation
The Radius parameter in the Unsharp Mask method determines the size of the sharpening radius, affecting the spread of the sharpening effect around the edges.
How can you minimize the risk of over-sharpening a street photography image?
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Use a sharpening method that allows for precise control
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Apply sharpening selectively to specific areas of the image
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Start with a low sharpening amount and gradually increase it until the desired result is achieved
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All of the above
D
Correct answer
Explanation
To minimize the risk of over-sharpening, use a sharpening method that allows for precise control, apply sharpening selectively to specific areas of the image, and start with a low sharpening amount and gradually increase it until the desired result is achieved.
Which of the following is not a common sharpening technique used in street photography?
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Unsharp Mask
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High Pass Filter
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Median Filter
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Smart Sharpen
C
Correct answer
Explanation
Median Filter is a noise reduction technique and not a sharpening technique commonly used in street photography.
What is the primary difference between Unsharp Mask and High Pass Filter sharpening methods?
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Unsharp Mask sharpens edges, while High Pass Filter sharpens details
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Unsharp Mask sharpens the entire image, while High Pass Filter sharpens only the high-frequency areas
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Unsharp Mask is more suitable for street photography, while High Pass Filter is more suitable for landscape photography
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Unsharp Mask is more computationally intensive than High Pass Filter
A
Correct answer
Explanation
Unsharp Mask primarily sharpens edges, while High Pass Filter sharpens details by enhancing the high-frequency areas of the image.
Which of the following is a common change detection technique that involves comparing two or more images of the same area taken at different times?
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Image Differencing
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Image Ratioing
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Principal Component Analysis
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Vegetation Index Differencing
A
Correct answer
Explanation
Image differencing involves subtracting the pixel values of two images taken at different times to highlight changes in the scene.
What is the fundamental principle behind image ratioing for change detection?
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Dividing the pixel values of two images
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Subtracting the pixel values of two images
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Multiplying the pixel values of two images
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Taking the absolute difference between pixel values
A
Correct answer
Explanation
Image ratioing involves dividing the pixel values of two images to highlight changes in the scene.