In this article, we will explore the concept of JPEG compression and its importance in the context of Raspberry Pi. As Raspberry Pi is a popular platform for image processing and computer vision applications, understanding JPEG compression is crucial for optimizing storage space and transmission bandwidth. We will also discuss how to utilize the Raspberry Pi's hardware capabilities to efficiently handle JPEG compression and decompression tasks.

Examples:

1. Basic JPEG Compression: To compress an image using JPEG on Raspberry Pi, we can utilize the "libjpeg" library. Here's an example code snippet in Python:

   import cv2
   
   # Load the image
   image = cv2.imread("input.jpg")
   
   # Compress the image using JPEG format
   quality = 90  # Adjust the compression quality (0-100)
   encode_param = [cv2.IMWRITE_JPEG_QUALITY, quality]
   _, compressed_image = cv2.imencode(".jpg", image, encode_param)
   
   # Save the compressed image
   cv2.imwrite("output.jpg", compressed_image)

2. Hardware-Accelerated JPEG Compression: Raspberry Pi's GPU provides hardware acceleration for JPEG compression and decompression. To leverage this capability, we can use the "picamera" library. Here's an example code snippet in Python:

   import picamera
   
   # Capture an image using Raspberry Pi Camera
   with picamera.PiCamera() as camera:
      camera.resolution = (640, 480)
      camera.capture("input.jpg")
   
   # Compress the captured image using hardware-accelerated JPEG
   with open("input.jpg", "rb") as file:
      compressed_image = camera.image_encoder.encode(file, quality=90)
   
   # Save the compressed image
   with open("output.jpg", "wb") as file:
      file.write(compressed_image)