Best Photo Editing Tools to Buy in February 2026

1

InPaint 9 - Remove objects and people from photos - Image editor compatible with Windows 11, 10, 8.1, 7

• EFFORTLESSLY REMOVE UNWANTED OBJECTS AND PEOPLE FROM PHOTOS!
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2

PhotoPad Photo Editing Software - Edit, Crop, Rotate, Touch-up or Apply Effects [Download]

• EFFORTLESSLY ENHANCE PHOTOS WITH INTUITIVE EDITING TOOLS.
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3

CorelDRAW Graphics Suite 2025 | Education Edition | Graphic Design Software for Professionals | Vector Illustration, Layout, and Image Editing [PC/Mac Download]

• CREATE STUNNING DESIGNS WITH ADVANCED PRINT AND PDF OPTIONS.
• ENHANCE PHOTOS AND GRAPHICS USING AI-POWERED EDITING TOOLS.
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4

Adobe Photoshop | Photo, Image, and Design Editing Software | 1-Month Subscription with Auto-Renewal, PC/Mac

• MUST COMPLETE CURRENT TERM BEFORE ADDING NEW SUBSCRIPTION.
• CREATE STUNNING GRAPHICS, PHOTOS, AND 3D ARTWORK WITH PHOTOSHOP.
• DESIGN APPS, EDIT VIDEOS, AND SIMULATE REAL-LIFE PAINTINGS EASILY.

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5

Corel Photo Video Ultimate Bundle 2023 | PaintShop Pro 2023 Ultimate and VideoStudio Ultimate 2023 | Powerful Photo and Video Editing Software [PC Download]

• UNLOCK PRO-LEVEL PHOTO AND VIDEO EDITING WITH INTUITIVE, POWERFUL TOOLS.
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• NO SUBSCRIPTION NEEDED-ENJOY ALL SKILL LEVELS WITH HELPFUL RESOURCES!

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6

CyberLink PowerDirector 2026 | Easily Create Videos Like a Pro | Intuitive AI Video Editing for Windows | Visual Effects, Slideshow Maker & Screen Recorder | Box with Download Code

• CAPTURE DUAL SCREENS & WEB CAMS; EXPORT CLIPS FOR EASY EDITING.
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• USE AI TO REMOVE BACKGROUNDS AND ADD AUTO CAPTIONS EFFORTLESSLY.

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7

Adobe Photoshop | Photo, Image, and Design Editing Software | 12-Month Subscription with Auto-Renewal, PC/Mac

• TRANSITION TO NEW SUBSCRIPTION ONLY AFTER CURRENT TERM ENDS.
• UNLEASH CREATIVITY WITH POWERFUL PHOTO AND 3D DESIGN TOOLS.
• ENHANCE MULTIMEDIA PROJECTS: EDIT VIDEOS AND DESIGN APPS SEAMLESSLY.

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8

GIMP Photo Editor 2026 + Office Suite LibreOffice 2026 on CD DVD Disc | Compatible with Microsoft Office Word Excel & PowerPoint | One Time Purchase, Lifetime License & Free Updates | Windows PC & Mac

• FULL COMPATIBILITY WITH MICROSOFT OFFICE AND PHOTOSHOP FILES!
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9

CorelDRAW Graphics Suite 2025 | Graphic Design Software for Professionals | Vector Illustration, Layout, and Image Editing [PC/Mac Download]

• UNLOCK CREATIVITY: ADVANCED PRINT TO PDF & ENHANCED BRUSH TOOLS.
• MASTER DESIGNS: LAYER-BASED EDITING & AI-DRIVEN IMAGE ENHANCEMENTS.
• SEAMLESS INTEGRATION: EXTENSIVE FILE SUPPORT FOR ALL YOUR PROJECTS.

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10

Pinnacle Studio Ultimate Video and Photo Bundle 2023 | Pinnacle Studio 26 Ultimate and PaintShop Pro 2023 plus exclusive collection of motion graphics, overlays, and scripts | [PC Download]

• COMPLETE MEDIA SUITE: VIDEO EDITING, PHOTOS, AND ANIMATIONS IN ONE BUNDLE!

• PRO-LEVEL EDITING TOOLS: MASTER HD, 4K, AND 360° VIDEOS EFFORTLESSLY!

• AI-POWERED EFFICIENCY: SPEED UP PHOTO EDITS WITH TIME-SAVING SCRIPTS!

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ONE MORE?

To blur an image in Julia, you can use the Images.jl package. First, you need to load the image you want to blur using the load function. Next, you can apply a blurring filter to the image using functions such as imfilter or imfilter!. These functions allow you to apply various kernel filters, such as Gaussian blur or box blur, to the image. Experiment with different filter sizes and magnitudes to achieve the desired blur effect. Finally, you can save the blurred image using the save function. Remember to install the Images.jl package if you haven't already by running Pkg.add("Images") in the Julia REPL.

How to blur an image to add a surreal touch in Julia?

To blur an image in Julia, you can use the Images package. Here is a simple example to blur an image and add a surreal touch:

1. Install the Images package by running the following command in Julia:

using Pkg Pkg.add("Images")

1. Load the Images package and read the image you want to blur:

using Images

Load the image

img = load("image.jpg")

1. Apply a blur filter to the image using the imfilter function with a Gaussian filter kernel:

using ImageFiltering

Apply Gaussian blur

blurred_img = imfilter(img, KernelFactors.gaussian(10))

1. Display the blurred image:

using ImageView

imshow(blurred_img)

You can adjust the size of the Gaussian filter kernel (10 in this example) to control the amount of blur in the image. Experiment with different kernel sizes to achieve the desired surreal effect.

How to simulate a rainy effect on an image using blur in Julia?

To simulate a rainy effect on an image using blur in Julia, you can use the Images.jl package which provides a powerful set of tools for image processing. Here is a step-by-step guide on how to achieve this effect:

1. Install the Images package if you haven't already by running the following command in the Julia REPL: using Pkg; Pkg.add("Images")
2. Load the necessary packages:

using Images using FileIO

1. Load the image you want to apply the rainy effect to:

image = load("path/to/image.jpg")

1. Create a function to simulate the rain effect using blur:

function apply_rain_effect(img::AbstractMatrix; intensity::Int = 20) randx = (rand(Int[] .- 1:1,size(img)) .== 1) randy = (rand(Int[] .- 1:1,size(img)) .== 1) img[randx] = 255 img[randy] = 255 return imfilter(img, Kernel.gaussian(intensity)) end

1. Apply the rain effect to the image:

rainy_image = apply_rain_effect(channelview(image); intensity = 20)

1. Display the rainy image:

display(rainy_image)

By following these steps, you should be able to simulate a rainy effect on an image using blur in Julia. Feel free to adjust the intensity parameter in the apply_rain_effect function to control the amount of blurring applied to the image.

How to blur an image on a specific axis using Julia?

You can blur an image on a specific axis in Julia by applying a filter kernel to the image using the Images and ImageFiltering packages. Here's a step-by-step guide to blur an image on a specific axis:

1. Install the required packages by running the following commands in Julia's REPL:

using Pkg Pkg.add("Images") Pkg.add("ImageFiltering")

1. Load the required packages:

using Images using ImageFiltering

1. Read the image file you want to blur:

img = load("image.jpg")

1. Define a filter kernel for blurring the image on a specific axis. For blurring on the x-axis, you can use a horizontal Gaussian filter kernel:

filter_kernel = Kernel.gaussian(5)

1. Blur the image on the x-axis using the imfilter function from the ImageFiltering package:

blurred_img = imfilter(img, filter_kernel, Fill(0), Reflect())

1. Display the blurred image:

display(blurred_img)

By following these steps, you can blur an image on a specific axis in Julia. You can adjust the filter kernel size and type to control the amount and direction of blurring applied to the image.

How to create a dreamy effect on an image using blur in Julia?

To create a dreamy effect on an image using blur in Julia, you can use the ImageFiltering.jl package. Here's a step-by-step guide on how to achieve this:

1. Install the ImageFiltering.jl package by running the following command in the Julia REPL:

using Pkg Pkg.add("ImageFiltering")

1. Load the necessary packages:

using Images using ImageFiltering

1. Load the image you want to apply the dreamy effect to:

img = load("path/to/your/image.jpg")

1. Apply a Gaussian blur to the image to create a dreamy effect:

blurred_img = imfilter(img, Kernel.gaussian(10))

In the above code, Kernel.gaussian(10) specifies the size of the blur kernel. You can adjust the kernel size to control the amount of blur applied to the image.

1. Display the original and blurred images:

display(img) display(blurred_img)

That's it! You have successfully created a dreamy effect on an image using blur in Julia. You can further customize the effect by adjusting the blur kernel size or trying out different types of blur filters provided by the ImageFiltering.jl package.

How to blur an image to create a hazy atmosphere in Julia?

To create a hazy atmosphere by blurring an image in Julia, you can use the Images package. Here's an example code snippet to blur an image and create a hazy effect:

using Images

Load the image

img = load("path_to_your_image.jpg")

Blur the image using the Gaussian kernel

blurred_img = imfilter(img, KernelFactors.gaussian(5))

Display the blurred image

display(blurred_img)

In this code snippet, we first load the image using the load function from the Images package. Then, we apply a Gaussian blur to the image using the imfilter function with a Gaussian kernel of size 5. Finally, we display the blurred image using the display function.

You can adjust the size of the Gaussian kernel (in this case, 5) to control the amount of blur applied to the image. Play around with different kernel sizes to achieve the desired hazy effect.