Its objective is to reduce the redundancy of the image and to store or transmit data in an efficient form.image croppingimage resizingimage compression

The objective you've outlined pertains to data handling techniques related to images: specifically, reducing redundancy and efficiently storing or transmitting data. Here’s a detailed explanation of the key concepts you mentioned:

1. Image Cropping: This technique involves removing unwanted outer areas of an image. By cropping, the focus can be placed directly on the subject of interest, thus reducing the image size and the amount of data that must be processed or transmitted. Additionally, it can improve data transmission speeds as the amount of data sent is less, which is particularly beneficial in low-bandwidth scenarios.

2. Image Resizing: Resizing an image changes its dimensions (width and height). This can lead to a decrease in file size since the number of pixels in the image is reduced. Resizing is particularly useful when images need to fit specific formats on websites or applications, where overly large images can slow down load times and require more storage space.

3. Image Compression: This is perhaps the most effective method for reducing redundancy in images. Compression algorithms reduce the file size by eliminating unnecessary or redundant data. There are two main types of compression: lossless and lossy. Lossless compression retains all the original data, allowing for a perfect reconstruction of the image, while lossy compression removes some data permanently, which can significantly reduce file sizes at the expense of image quality.

Together, these techniques combine to create a more efficient method for handling images in terms of storage and transmission, ensuring that data can be utilized and shared more effectively.