Q1. In an 8-bit color image, the intensity value (255,255,255) corresponds to which color? (Consider the RGB color model here)
Black
White
Red
Cyan
Answer: 2 Explanation: Because RGB is an additive color model i.e. the colors present in the light add to form new colors. So, Zero intensity for each component(RGB) gives the darkest color (no light, considered the black), and full intensity of each gives a white. Since for an 8-bit image the full intensity value is 255 so the answer is White. Refer to this link to know more.
Q2. Which of the following techniques can be used for blur detection or detecting blurred images?
Variance of Laplacian
Unsharp Masking
High Boost filtering
All of the above
Answer: 1 Explanation: As we all know that the blurry image doesn’t have well-defined edges. So, if you calculate the Laplacian of this image, you will get more or less the same response everywhere. In other words, the variance of this Laplacian image will be less. So, this can be used for blur detection.
Q3. Which of the following can be a reason for a low contrast image?
Poor illumination of the scene
wrong setting of lens aperture during image acquisition
lack of dynamic range in the imaging sensor
All of the above
Answer: 4 Explanation: All of the above can be possible reasons for getting a low contrast image.
Q4. For which type of images, the Histogram Equalization technique can be used?
thermal images
Satellite images
X-ray images
All of the above
Answer: 4 Explanation: Because Histogram Equalization is a contrast enhancement method so this can be used in all of the above images.
Q5. Which of the following OpenCV functions can be used to perform the Dilation operation?
cv2.dilate()
cv2.Dilate()
cv2.dilate2D()
cv2.morphDilate()
Answer: 1 Explanation: In OpenCV, cv2.dilate() can be used to perform Dilation operation. Refer to this link to know more.
Q6. Generally in a 1D image histogram, what do the x and y-axis represents?
x-axis: Intensity values, Y-axis: no. of pixels corresponding to intensity values
x-axis: no. of pixels corresponding to intensity values, Y-axis: Intensity values
x-axis: pixel location, y-axis: Intensity values
x-axis: Intensity values, y-axis: pixel location
Answer: 1 Explanation: In 1D image histogram, we plot the intensity values on the x-axis and the no. of pixels corresponding to intensity values on the y-axis. To know more about Image Histograms, refer to this link.
Q7. What of the following is the general form of representation of log transformation? Suppose r and s denote the input and output pixel values respectively.
s=clog10(1/r)
s=clog10(1+r)
s=clog10(1-r)
s=clog10(1*r)
Answer: 2 Explanation: Log transformation means replacing each pixel value with its logarithm. The general form of log transformation function is given by s=clog10(1+r). Refer to this link to know more.
Q8. What is a high pass filter?
a filter that enhances the high-frequency parts of an image
a filter that enhances the low-frequency parts of an image
Answer: 1 Explanation: A high pass filter is the one that enhances the high-frequency parts of an image.