image analysis and visualization in Python with scikit-image, napari, and friends | SciPy 2023

Explore the world of image analysis and visualization in Python with scikit-image, napari, and friends, covering topics like Gaussian filters, convolution, and more.

Key takeaways

Image Analysis and Visualization with Python

  • Gaussian Filter: A Gaussian filter is used to smooth an image, which can help remove noise and reduce the intensity of the signal.
  • Convolution: Convolution is a mathematical operation that applies a kernel to an image to produce a new image.
  • Kernel: A kernel is a small matrix that is used to perform a mathematical operation on an image.
  • Image Segmentation: Image segmentation is the process of partitioning an image into its constituent parts or objects.
  • Watershed Transform: The watershed transform is an algorithm used to separate objects in an image based on their intensity values.
  • Napari: Napari is a Python library that provides an interactive 3D viewer for images.
  • Image Morphology: Image morphology is the study of the shape and structure of images.
  • Region Propagation: Region propagation is a technique used to extract information from an image by labeling pixels based on their intensity values.
  • Intensive Color: Intensive color is a color that is not dependent on the background, but rather on the color itself.
  • Scikit-image: Scikit-image is a Python library for image processing and analysis.
  • RGB (Red, Green, Blue): RGB is a color model that uses three primary colors to create a wide range of colors.
  • RGBA (Red, Green, Blue, Alpha): RGBA is a color model that adds an additional channel to the RGB model for transparency.
  • Thresholding: Thresholding is a method of image segmentation that separates an image into two or more regions based on a threshold value.
  • Minimum and Maximum Values: The minimum and maximum values of an image can be used to determine the range of intensity values within the image.
  • Scipy: Scipy is a Python library for scientific computing and image processing.
  • numpy: NumPy is a Python library for numerical computation.
  • Polar Representation: Polar representation is a way of representing a 2D image in a 1D format using polar coordinates.
  • Intensity Values: Intensity values are the numerical values that represent the brightness of each pixel in an image.
  • Image Denoising: Image denoising is the process of removing noise from an image.
  • De-Noising: De-noising is the process of removing noise from an image.
  • Gaussian Blurring: Gaussian blurring is a technique used to reduce the noise in an image by convolving it with a Gaussian kernel.
  • Median Filter: A median filter is a digital filter that replaces each pixel with the median value of the neighboring pixels.
  • Anisotropic Diffusion: Anisotropic diffusion is a technique used to denoise an image by performing a series of operations that refine the image in a direction perpendicular to the edges.
  • Iterative Algorithm: An iterative algorithm is an algorithm that repeats a set of instructions until a desired result is achieved.
  • Grid-Based Algorithm: A grid-based algorithm is an algorithm that uses a grid to organize and manipulate an image.
  • Image Processing: Image processing is the process of modifying an image to achieve a specific goal.
  • Computer Vision: Computer vision is the field of study that deals with enabling computers to see and understand the world visually.
  • Data Visualization: Data visualization is the process of creating a visual representation of data.
  • Interactive Visualization: Interactive visualization is a form of data visualization that allows the user to interact with the data.
  • Nepari: Nepari is a Python library that provides an interactive 3D viewer for images.
  • Scikit-image installation: Scikit-image can be installed using pip, the Python package manager.
  • Numpy installation: NumPy can be installed using pip, the Python package manager.
  • OpenCV installation: OpenCV can be installed using pip, the Python package manager.
  • Pillow installation: Pillow can be installed using pip, the Python package manager.
  • matplotlib installation: Matplotlib can be installed using pip, the Python package manager.