Java Image Processing: Data Migration and Archival Efficiency

Managing high volumes of high-resolution images is a double-edged sword. While the data is invaluable for research, manufacturing, and documentation, the sheer scale of storage required can quickly become a massive financial and technical burden.

The Growing Crisis of “Too Much Data”

When an organization generates hundreds of thousands of high-resolution images annually, as seen in large-scale manufacturing and scientific research, the strain on infrastructure is immediate. Whether it’s an Oracle database reaching its limit or a server cluster running out of physical disk space, the cost of buying more storage, eventually hits a point of diminishing returns.

We saw this clearly with one of our enterprise clients. They were generating a massive volume of high-resolution pictures, and the storage costs within their database were spiralling.

They didn’t just need to compress the files; they needed to do so without losing a single pixel of data integrity.

The Accessibility Barrier: When Files Are Locked Away

Storage is only half the battle. The other half is accessibility. Another enterprise client in the research and development space faced a different but related struggle. They needed to share JPEG 2000 radiographs with their nuclear emergency response community.

Because standard browsers don’t natively support JPEG 2000, users were forced to download the files and open them in external software. In a high-stakes environment, this extra step isn’t just an inconvenience, it’s a critical delay.

The Search for a Better Way

Both organizations faced a choice:

• Build in-house: Spend months of specialized engineering time trying to master complex image compression.
• Buy more hardware: Keep throwing money at the storage problem without solving the root cause.
• Find a drop-in solution: Find a tool that integrates seamlessly with their existing Java environment.

Bridging the Gap with Smart Compression and Native Support

The turning point came when these organizations moved toward a more agile Java-based approach.

For the company handling hundreds of thousands of images in their Oracle database, the answer was lossless WebP compression.

By switching to a modern format that maintains perfect data integrity while significantly reducing file size, they achieved a 25% reduction in storage space. This wasn’t just a technical win; it was a massive cost saving that deferred the need for expensive new hardware.

For another enterprise, the solution was about removing friction. By dropping a specialized image library into their system, they enabled their web applications to handle JPEG 2000 images natively.

JDeli’s convert API helped them automate JPEG 2000 conversion to JPEG. Suddenly, the emergency response community could view critical radiographs directly in their browser, no external software required.

Technical Implementation: Solving the Storage and Display Gap

Below are the simple step-by-step guides that helped clear these problems in a Java environment.

Code Example: Converting Images to Lossless WebP for Storage Efficiency

In this code example, we use JDeli’s WebP Encoder which is written 100% in Java.

1. Add JDeli to Your Project: Add JDeli to your class or module path. (download the trial jar ).
2. Create the options object

final WebpEncoderOptions options = new WebpEncoderOptions();

3. Configure the options (can be done at any time before writing)

options.setCompressionFormat(WebpCompressionFormat.LOSSLESS);

4. Write the image (can be done later, even in a different method)

JDeli.write(myBufferedImage, options, outputStreamOrFile);

Performance Comparison

Below you can see performance comparison against ImageIO:

You can read more about how these tests were conducted here.
 

Code Example: Reading and Displaying JPEG 2000 Images in a Web Context

This code example will show you how to convert JPEG 2000 to JPG in a pure java.

1. Add JDeli to Your Project: Add JDeli to your class or module path. (download the trial jar ).
2. Read JPEG2000 image into Java

BufferedImage bufferedImage = JDeli.read(new File("jpxImageFile.jpx"));

3. Process image if needed (scale, sharpen, lighten, watermark, etc)

bufferedImage = operations.apply(BufferedImage bufferedImage); // Optional

4. Write out BufferedImage as JPG image file

JDeli.write(bufferedImage, "jpg", new File("jpgImageFile.jpg"));

You can read more about how these tests were conducted here.

The Strategic Impact

By moving away from “brute force” storage methods and embracing modern image standards, these organizations did more than just save disk space. They increased the speed of their workflows, ensured long-term data integrity, and reduced the maintenance burden on their IT teams.

When you solve the storage problem at the software level, you’re not just managing files, you’re optimizing the entire lifecycle of your organization’s most valuable data.

// Read an image
BufferedImage bufferedImage = JDeli.read(avifImageFile);

// Write an image
JDeli.write(bufferedImage, "avif", outputStreamOrFile);

// Read an image
BufferedImage bufferedImage = JDeli.read(dicomImageFile);

// Read an image
BufferedImage bufferedImage = JDeli.read(heicImageFile);

// Write an image
JDeli.write(bufferedImage, "heic", outputStreamOrFile);

// Read an image
BufferedImage bufferedImage = JDeli.read(jpegImageFile);

// Write an image
JDeli.write(bufferedImage, "jpeg", outputStreamOrFile);

// Read an image
BufferedImage bufferedImage = JDeli.read(jpeg2000ImageFile);

// Write an image
JDeli.write(bufferedImage, "jpx", outputStreamOrFile);

// Write an image
JDeli.write(bufferedImage, "pdf", outputStreamOrFile);

// Read an image
BufferedImage bufferedImage = JDeli.read(pngImageFile);

// Write an image
JDeli.write(bufferedImage, "png", outputStreamOrFile);

// Read an image
BufferedImage bufferedImage = JDeli.read(tiffImageFile);

// Write an image
JDeli.write(bufferedImage, "tiff", outputStreamOrFile);

// Read an image
BufferedImage bufferedImage = JDeli.read(webpImageFile);

// Write an image
JDeli.write(bufferedImage, "webp", outputStreamOrFile);