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How To Automatically Improve Image Resolution

improve image resolution

Using image enhancement tools can help you create visually stunning content that resonates with your audience. With so much competition for attention, it’s more important than ever to make sure your visuals stand out. Improving the image resolution is a key aspect of making your visuals stand out.

To achieve this for just a few images, a variety of advanced tools and techniques are available and commonly used by non developers. For instance, VanceAI Image Enhancer offers a one-click AI solution that sharpens details, adjusts color, and enhances resolution. Adobe Photoshop’s Super Resolution feature can significantly increase image resolution, while Adobe Photoshop Lightroom provides features like Denoise, Raw Details, and Super Resolution to further refine image quality.

Additionally, online tools like AI Image Enlarger can sharpen, denoise, retouch, remove backgrounds, and increase image size effectively. Specific AI-driven tools such as AI Denoiser, AI Sharpener, and BeFunky can also be employed for tasks like noise removal, sharpening soft edges, balancing exposure, enhancing details, and boosting color. Adjusting an image’s saturation settings can further enhance colors, making them brighter and bolder. 

These tools, however, do not provide a scalable nor code-first solution.

Higher resolution images translate to greater detail, clarity, and vibrancy, making them more visually appealing and engaging to the viewer. They’re essential for maintaining quality across other mediums. By improving image resolution, you ensure that your visuals are versatile and adaptable across different platforms, maintaining their impact and effectiveness no matter how they’re viewed.

In this article, we’ll look at how to use cutting-edge features to automatically enhance image resolution so you can easily improve the quality of your images.

In this article:

Why Is It Important to Improve Image Resolution?

There are a variety of reasons that you may need to improve the resolution of your images. First off, high-quality images are necessary for developing a credible and eye-catching online profile. Low-resolution pictures may appear pixelated, blurry, or distorted, which can diminish the quality of your content and turn off your audience.

Second, you’ll need higher-quality images if you want the ability to print them out or use them in large format displays like billboards, posters, or banners. When blown up to larger sizes, low-resolution pictures will appear stretched and pixelated, which can significantly reduce their impact and quality.

Finally, picture resolution can impact how your website loads and overall performance. Large, high-resolution images may cause website load times to increase, which may harm user experience and search engine rankings.

When Might You Need to Improve Image Resolution?

Having high-resolution images is essential to your user’s viewing experience. But you may not always have access to these images at the start. There are plenty of situations where you may need to improve image resolution, such as:

  • When dealing with low-resolution or pixelated images, increasing their resolution can help to improve their quality and give them a more professional appearance.
  • If users need to print images or use them in large displays, you’ll need to ensure the resolution is good enough to preserve the quality and clarity at bigger sizes. Examples of large-format displays include billboards and banners.
  • Creating visually appealing websites, social media posts, and online ads that grab your audience’s attention requires high-quality images.
  • High-resolution images are necessary for creating prints, designs, and pictures that satisfy professional graphic design and photography standards.

Tips for Achieving the Best Results by Automatically Improving Image Resolution

There are a plethora of ways to improve image resolution. However, not all are created equal; some may need more work than others. We’ve got a list of some of our best tips to get you the best results:

  1. Choose the Right Image Upscaling Tool: The first step to achieving the best results with automatic image upscaling is to choose the right tool for the job. Look for a tool that can produce high-quality results and is easy to use with intuitive controls and options.
  2. Start with High-Quality Source Images: The quality of your source image will affect the results of your upscaling. Start with the highest quality source image possible, preferably at least 2-3 times larger than the desired output size.
  3. Adjust Your Settings: Most automatic image upscaling tools will offer presets or custom settings that you can use to fine-tune your results. Experiment with different settings to find the best ones for your image and output size.
  4. Avoid Over-Processing: While it can be tempting to push your image upscaling to the limit, it’s important to avoid over-processing. Over-processing can lead to artifacts, noise, and other unwanted effects on your image. Instead, aim to balance sharpness, detail, and noise reduction.
  5. Compare Before and After Results: It’s always a good idea to compare your before and after results to ensure you achieve the best possible output. Use the zoom feature to closely examine the details and quality of your image and make any necessary adjustments to your settings as needed.
  6. Use Additional Editing Techniques: While automatic image upscaling can produce impressive results, you can take your image to the next level by using additional editing techniques such as color correction, sharpening, and noise reduction.

By following these tips and techniques, you can achieve the best possible results with automatic image upscaling and create high-quality visuals that enhance your online presence and engage your audience.

How to Improve Image Resolution Programmatically

If you’re dealing with low-resolution images on your website or application, manually enhancing their quality can be frustrating and time-consuming. Let’s look at how you can take advantage of Cloudinary’s advanced image transformation features to boost the quality of your images on the fly without compromising performance or user experience.

Pre-requisites

The first step to improving image resolution is to create a free account. Once your account is up and ready, the next step will be to install the latest version of Node.js on your computer. If you don’t have Node.js installed on your device, you can download it for free from the official Node.js website.

In order to authenticate and make API requests to the cloud, we’ll be using the Cloudinary Node.js SDK. This library can be installed by creating a project folder in any directory of your choice and running the following command in your terminal while in your project directory:

npm install cloudinary

Now we’re able to make API calls to the cloud, so let’s move to the next step.

Enhance Images with AI Using VIESUS™

Before we begin, it’s important to note that we’ll use the VIESUS Automatic Image Enhancement addon in Cloudinary before calling the API. This add-on utilizes artificial intelligence and machine learning algorithms to automatically enhance the quality of your images, making them sharper, more vibrant, and more detailed.

We must subscribe to the VIESUS Automatic Image Enhancement service to use this add-on, so log in to your account and head to the add-on tab:

Select add on tab

Next, search for the VISUS Image Enhancement add-on:

Image enhancement

Click on the add-on and subscribe to the free plan:

Subscribe to free plan

Now that we have everything, we can start enhancing the resolution of our images programmatically using the API. First, let’s create an assets folder in our project directory. Here we will define the images we want to enhance. For now, we will be using sheep.jpg:

Define image to enhance

Now, open up the project folder in your favorite IDE, and create a new file named viesus.js. Open up the file and start by importing the Node.js SDK and defining our API with our account details:

const cloudinary = require('cloudinary').v2;

// Replace with your CLOUD_NAME, API_KEY, and API_SECRET
cloudinary.config({
    cloud_name: 'CLOUD_NAME',
    api_key: 'API_KEY',
    api_secret: 'API_SECRET' 
  });

Next, we use the cloudinary.uploader.upload() function to upload the local file to the cloud. This uploads the image file to Cloudinary’s servers. For now, we are uploading sheep.jpg located in the assets folder of our project:

// Enhance Image Resolution using VIESUS
cloudinary.uploader
.upload("assets/sheep.jpg",
  { public_id: "sheep",
    eager: { effect: "viesus_correct", crop: "scale", width: 400 }})
.then(result=>console.log(result));

Next, in the options object, we specify the public ID for the uploaded image as "sheep", and the transformation to apply as eager.

eager is an optional parameter that allows you to specify any image transformations that should be performed immediately after the image is uploaded. In this case, it includes the effect of "viesus_correct", which uses VIESUS to enhance the image quality.

Additionally, we set the crop parameter is set to "scale", which resizes the image while preserving its aspect ratio, and the width parameter is set to 400, which sets the width of the image to 400 pixels.

Finally, we use Promise to log the upload result to the console. Here is what our final code looks like:

const cloudinary = require('cloudinary').v2;

// Replace with your CLOUD_NAME, API_KEY, and API_SECRET
cloudinary.config({
    cloud_name: 'CLOUD_NAME',
    api_key: 'API_KEY',
    api_secret: 'API_SECRET' 
  });

// Enhance Image Resolution using VIESUS
cloudinary.uploader
.upload("assets/sheep.jpg",
  { public_id: "beach",
    eager: { effect: "viesus_correct", crop: "scale", width: 400 }})
.then(result=>console.log(result));

Now you can simply run the code using Node:

node viesus.js

Node vs js

To verify your upload, you can either follow the URL given in the terminal output or head on to the Media Library tab on your Cloudinary account:

Select

Here is a before and after of our image:

Before and after image

As you can see, the brightness of our image is increased, and the colors appear more vivid, while the photo now looks like it was taken on a bright sunny day with more natural colors. In contrast, the original image has darker colors and highlights that seem overexposed.

Using the Super Resolution Feature

Cloudinary’s Super Resolution is another powerful tool that allows you to increase the resolution and quality of your images without sacrificing detail or clarity. This feature is especially useful for low-quality or low-resolution images, such as those captured on older devices or with lower-end cameras.

Normally, when you upscale an image, it will lose its quality and detail. For example, take a look at this tall-hall.jpg image. The image is 200 x 303 pixels:

Image

If you upscale such an image, it will lose clarity. With Super Resolution, you can retain much more detail for the same scaling factor.

Let’s begin by adding this image to our asset folder. Next, in your project folder, create a new file named super_resolution.js. As before, start by importing the Node.js SDK and defining our API.

const cloudinary = require('cloudinary').v2;

// Replace with your CLOUD_NAME, API_KEY, and API_SECRET
cloudinary.config({
    cloud_name: 'CLOUD_NAME',
    api_key: 'API_KEY',
    api_secret: 'API_SECRET' 
  });

Next, we simply call the uploader API method to upload our image with our desired effect:

// Super Resolution
cloudinary.uploader.upload("assets/tall-hall.jpg", {
    public_id: 'tall-hall',
    eager: [
        { effect: "upscale" },
        {width: "4.0", crop: "scale"}
    ]
})

After the upload is complete, we can use the then() method to generate the URL for the new image:

.then(result => {
    const imageUrl = cloudinary.url(result.public_id, {
        secure: true,
        transformation: [
            { effect: "upscale" },
            {width: "4.0", crop: "scale"}
        ]
    });
    console.log(imageUrl);
});

Here we use the url() method to generate the URL by providing the public ID of the image and the desired transformation(s).

The transformation specified in the eager parameter and the url() method requests the upscale effect. It applies Super Resolution to our image and scales it to 4 times the original image’s width. The crop parameter is also set to "scale", which scales the image proportionally to the specified width without cropping it.

Here is what our final code looks like:

const cloudinary = require('cloudinary').v2;

// Replace with your CLOUD_NAME, API_KEY, and API_SECRET
cloudinary.config({
    cloud_name: 'CLOUD_NAME',
    api_key: 'API_KEY',
    api_secret: 'API_SECRET' 
  });

// Super Resolution
cloudinary.uploader.upload("assets/tall-hall.jpg", {
    public_id: 'tall-hall',
    eager: [
        { effect: "upscale" },
        {width: "4.0", crop: "scale"}
    ]
}).then(result => {
    const imageUrl = cloudinary.url(result.public_id, {
        secure: true,
        transformation: [
            { effect: "upscale" },
            {width: "4.0", crop: "scale"}
        ]
    });
    console.log(imageUrl);
});

Now you can simply run the code using Node:

node super_resolution.js

Node super resolution

To verify your upload, you can either follow the URL given in the terminal output or head on to the Media Library tab on your Cloudinary account:

Verify upload

Here is what our final image looks like:

Image

Final Thoughts

By providing powerful tools for automatically enhancing picture resolution, Cloudinary makes it simple to produce stunning, high-quality images that captivate your audience. Without any specialized expertise or abilities, you can improve your images with Cloudinary’s cutting-edge features and simple-to-use interface in just a few clicks.

Why wait? Sign up to Cloudinary today to improve your picture quality.

Learn more:

QUICK TIPS
Colby Fayock
Cloudinary Logo Colby Fayock

In my experience, here are tips that can help you better enhance image resolution automatically, ensuring you get high-quality results while optimizing your workflow:

  1. Pre-process images before upscaling for best results
    Start by applying basic adjustments such as noise reduction, sharpening, and contrast correction to your low-resolution images before upscaling. Pre-processing the image helps the upscaling algorithm perform more accurately, reducing artifacts and producing a cleaner, more detailed final output.
  2. Use targeted super-resolution for critical regions
    Instead of upscaling the entire image, identify key areas (e.g., faces, product details) and apply super-resolution selectively. This approach, known as region-specific enhancement, can save processing time and resources, and is particularly effective for applications like e-commerce, where product details need to be exceptionally clear.
  3. Optimize file size without sacrificing quality using auto:quality
    When using super-resolution features, file sizes can grow significantly. Utilize Cloudinary’s auto:quality parameter to dynamically balance file size and image quality. This setting intelligently reduces file size based on content, ensuring the upscaled image remains visually appealing without being overly large.
  4. Leverage batch processing for large-scale resolution enhancements
    Automate the enhancement of large image libraries using Cloudinary’s batch processing capabilities. By defining consistent transformation rules and applying them across multiple images in a single API call, you ensure uniform quality and save significant manual effort when processing thousands of assets.
  5. Combine upscaling with AI-based enhancements for professional results
    Tools like Cloudinary’s VIESUS™ Automatic Image Enhancement add-on can be combined with super-resolution techniques to achieve professional-quality images. Use VIESUS for AI-driven corrections in lighting, saturation, and color balance, then apply super-resolution to sharpen details—yielding a truly polished look.
  6. Use eager transformations for on-the-fly resolution adjustments
    If your application dynamically serves images of various resolutions, implement eager transformations to generate multiple resolutions upfront. By pre-generating multiple sizes using the eager parameter, you ensure fast delivery of the optimal image size based on device type, saving bandwidth and improving load times.
  7. Avoid excessive scaling to maintain natural appearance
    Upscaling by more than 2x-4x can result in an unnatural look, even with advanced algorithms. If you need extreme upscaling (e.g., turning a small icon into a high-res banner), consider using vector-based techniques or blending multiple AI models to avoid oversharpening and preserve the image’s natural feel.
  8. Employ content-aware cropping and padding for aesthetic consistency
    When upscaling images for applications like responsive design, cropping and padding may be required to fit certain aspect ratios. Use content-aware cropping to focus on important regions, and add padding to maintain visual balance. Cloudinary’s gravity: "auto" combined with crop: "fill" is ideal for automating this process.
  9. Integrate real-time image enhancement for user-generated content
    If your application handles user-generated images (e.g., social media platforms), implement real-time resolution enhancement using Cloudinary’s URL-based transformations. By automating the enhancement of user uploads, you maintain consistent quality and optimize image delivery across various devices.
  10. Document and monitor transformation performance to fine-tune settings
    Track and log the impact of each transformation on image quality, performance, and user engagement metrics. Use Cloudinary’s analytics tools to identify which parameters yield the best results for different image types and scenarios. Continuously fine-tune your transformation settings based on this data to achieve optimal results.

With these tips, you can effectively enhance image resolution while balancing performance, visual appeal, and resource usage. By leveraging advanced AI tools and optimizing your workflow, you’ll be able to produce high-quality images that are ready for any use case, from websites to large-scale print media.

Last updated: Oct 3, 2024