Vision Algorithms Quiz

What is histogram equalization and how does it improve image contrast?

• Histogram equalization is a process to convert images to grayscale

• Histogram equalization is a method to rotate images by 90 degrees

• Histogram equalization is a technique used to blur images by reducing contrast

• Histogram equalization is a technique used to improve the contrast of an image by redistributing the intensity values.

Explain the concept of gray level transformation in image processing.

• Gray level transformation is a technique used to adjust the brightness and contrast of an image by mapping the original pixel intensity values to a new range of values.

• Gray level transformation is a method to compress image files for storage purposes.

• Gray level transformation is a technique used to convert color images to black and white.

• Gray level transformation involves rotating images to adjust their orientation.

How are arithmetic operations used in pixel manipulation for image processing?

• Arithmetic operations are used to adjust pixel values for tasks like brightness, contrast, and color balance in image processing.

• Arithmetic operations are used to compress images.

• Arithmetic operations are used to rotate images.

• Arithmetic operations are used to add audio to images.

What are spatial domain filters and how do they enhance images?

• Spatial domain filters enhance images by directly manipulating pixel values through operations like smoothing, sharpening, and edge detection.

• Spatial domain filters enhance images by adding noise

• Spatial domain filters enhance images by changing the file format

• Spatial domain filters enhance images by adjusting the screen resolution

Describe the role of frequency domain filters in image processing.

• Frequency domain filters are only used for text processing

• Frequency domain filters play a crucial role in image processing by allowing manipulation of image frequency content to enhance features or remove noise.

• Frequency domain filters can only be applied to black and white images

• Frequency domain filters have no impact on image processing

What are some common image enhancement techniques used in low level vision algorithms?

• Gaussian blurring, color inversion, rotation transformation

• Histogram equalization, contrast stretching, noise reduction filters, sharpening filters, edge detection

How does histogram equalization help in adjusting the dynamic range of an image?

• Histogram equalization reduces the contrast of an image

• Histogram equalization changes the aspect ratio of an image

• Histogram equalization adjusts the dynamic range of an image by redistributing intensity values based on the cumulative distribution function of the histogram.

• Histogram equalization increases the saturation of an image

Discuss the importance of gray level transformation in image enhancement.

• Gray level transformation has no impact on image quality.

• Gray level transformation only affects color images.

• Gray level transformation is only useful for black and white images.

• Gray level transformation helps in enhancing image quality by adjusting contrast and brightness levels.

Give examples of arithmetic operations that can be performed on image pixels.

• Taking the square root of pixel values

• Concatenating pixel values together

• Applying a trigonometric function to pixel values

• Examples: Adding a constant value to all pixels, subtracting one image from another, multiplying pixel values by a scalar, dividing pixel values by a constant.

Explain the process of applying spatial domain filters to remove noise from images.

• Calculating new pixel values based on the original pixel values

• The process involves defining a filter mask, applying it to each pixel in the image, and calculating new pixel values based on the filter mask to remove noise.

• The process involves randomly selecting pixels to remove noise

• Applying a filter mask to only the edges of the image