A) Applying filters to an image. B) Analyzing the frequency components of an image. C) Converting an image to a different color space. D) Operations are performed directly on the pixels of an image.
A) Creating a 3D representation of an image. B) Detecting and recognizing objects in an image. C) Adjusting the contrast of an image. D) Dividing an image into multiple segments to simplify its representation.
A) Blurring the details in an image. B) Colorizing a black and white image. C) Identifying the boundaries of objects in an image. D) Morphing one image into another.
A) Converting a color image to grayscale. B) Adding noise to an image. C) Reducing the size of an image file while preserving its visual quality. D) Enlarging an image without losing quality.
A) The physical size of an image in pixels. B) The number of bits used to represent each pixel in an image. C) The aspect ratio of an image. D) The number of colors in an image.
A) Converting an image to black and white. B) Improving the contrast of an image by spreading out pixel values. C) Resizing an image. D) Adding noise to an image.
A) PNG B) BMP C) GIF D) JPEG
A) Expanding the boundaries of objects in an image. B) Reducing the size of objects in an image. C) Adding noise to an image. D) Changing the colors of an image.
A) Adding noise to an image. B) Resizing an image. C) Converting an image from one color representation to another. D) Adjusting the brightness of an image.
A) Manipulating the structure of objects in an image. B) Smoothing out the texture of an image. C) Enhancing the brightness of an image. D) Applying artistic filters to an image.
A) Histogram analysis B) Pixel averaging C) Lens distortion correction D) Optical Character Recognition (OCR)
A) Image classification and object detection. B) Creating image collages. C) Converting color images to black and white. D) Adding motion blur to images.
A) Median filtering B) Saturation adjustment C) Thresholding D) Dithering
A) Gradient descent B) Linear regression C) Principal component analysis D) K-means clustering
A) Detecting edges in an image. B) Finding a subimage within a larger image. C) Creating a collage from multiple images. D) Generating random images.
A) Detecting edges in an image. B) Rotating an image. C) Creating animations from still images. D) Converting an image from spatial domain to frequency domain. |