Podcast
Questions and Answers
What are the fundamental steps in image processing?
What are the fundamental steps in image processing?
Image acquisition, Sampling and quantization, Image representation, Image recognition
What are the basic relationships between pixels in image processing?
What are the basic relationships between pixels in image processing?
Neighbor's connectivity
What are the two color image models mentioned in the text?
What are the two color image models mentioned in the text?
RGB and CMY
What are the spatial domain image processing methods discussed?
What are the spatial domain image processing methods discussed?
Signup and view all the answers
What are the different types of image compression mentioned?
What are the different types of image compression mentioned?
Signup and view all the answers
Study Notes
Image Processing Fundamentals
- The fundamental steps in image processing are: image acquisition, image enhancement, image restoration, image compression, and image reconstruction.
Pixel Relationships
- Pixels are the basic units of a digital image, and each pixel has a specific value (intensity) which determines its brightness.
- Pixels are arranged in a 2D grid, with each pixel having a horizontal and vertical coordinate (x, y).
- The relationships between pixels are based on their spatial positioning, with neighboring pixels being those that are directly adjacent (horizontally, vertically, or diagonally) to a given pixel.
Color Image Models
- RGB (Red, Green, Blue) color model is an additive model, where the combination of red, green, and blue light produces the final color.
- CMYK (Cyan, Magenta, Yellow, Black) color model is a subtractive model, where the combination of cyan, magenta, and yellow inks absorbs certain wavelengths of light to produce the final color.
Spatial Domain Image Processing
- Spatial domain image processing methods operate directly on the pixels of the image, without transforming the image into another domain (e.g. frequency domain).
- Spatial domain methods discussed include: image negation, logarithmic transformation, and power-law transformation.
Image Compression
- Lossless compression: reduces the size of the image without losing any of the original data (e.g. Huffman coding, LZW coding).
- Lossy compression: reduces the size of the image by discarding some of the original data (e.g. JPEG compression).
Studying That Suits You
Use AI to generate personalized quizzes and flashcards to suit your learning preferences.
Description
Test your knowledge of digital image fundamentals, including image representation, resolution, image acquisition methods like X-ray imaging and MRI, spatial domain image processing methods, and more.
