What are the best practices for resizing and cropping images in editing software?

Resizing and cropping images are common tasks in image editing software, and there are several best practices to ensure you achieve the desired results while maintaining image quality: a). Use Non-Destructive Editing: b). Maintain Aspect Ratio: c). Resolution Consideration: d). Crop for Composition: e). Rule of Thirds: f). Use Gridlines or Guides: g). Preserve Originals: h). Check Image Quality: i). Save in the Appropriate Format: j). Experiment and Iterate: By following these best practices, you can effectively resize and crop images while maintaining their quality and achieving your desired visual outcome.

Always start with the highest resolution image available when resizing. Resizing down (reducing size) maintains more of the image's quality than resizing up (increasing size), which can result in pixelation or blur.

Do not mix up concepts (there are errors in the main text that is proposed here). The resolution is the number of pixels in the width and height of an image. ppi : it means "pixels per inch". It is the pixel density, which means how much pixels are used in a real-life distance (for example, if a physical card measuring 1 inch contains 96 pixels, it indicates it has 96 ppi). So there are three values, interconnected : resolution, pixel density, distance.

Best Practices for Choosing Interpolation Methods: For high-quality final outputs, especially in professional settings, prefer methods like bicubic or Lanczos over nearest neighbor or bilinear, unless speed is a critical factor. Sometimes, the best method depends on the specific image and how it responds to different interpolations. Don't hesitate to try a couple of methods to see which yields the best result for your needs. Familiarize yourself with the settings and options in your chosen editing software, as many programs offer customizable interpolation settings that can be adjusted for different scenarios.

Chosing the right interpolation is crucial, as a bad one can result in aliasing, or artifacts. Machine Learning methods achieve very good results, but need to be monitored, because sometimes it goes to far, and creates something that is too much away from reality.

Crop images to enhance composition, remove unnecessary elements, or focus on a specific part of the image. Think about the rule of thirds or leading lines to make the image more engaging.

Before making any changes, save a copy of the original image. This ensures that you have the original to fall back on if something goes wrong or if you need to make different adjustments later.

For the original image, always use a lossless format, for example exr. Do not use jpeg, as each save will lose some details inside the picture.

After resizing or cropping, be mindful of the file size and format. Larger files can slow down website load times, affecting user experience and SEO. Use formats like JPEG for a good balance of quality and file size for web use, and consider PNG for graphics with transparent backgrounds.

Comparing your current picture to the original one, allows to detect errors, for example if you have applied a wrong color correction, because you have lost (or applied twice) a LUT (Look Up Table) along steps of your process. Or maybe you have mixed two color modes : linear and logarithmic.

For web content, consider how your images will resize automatically across different screen sizes. You might need to create different versions of an image for desktop, tablet, and mobile views to ensure the best user experience.