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Tăng độ phân giải ảnh lên đến 4x bằng AI. Cải thiện chất lượng không pixel hóa.

Nâng cấp 4x AI Loại bỏ pixel hóa Cải thiện chi tiết
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Tối đa 100 MB miễn phí • Định dạng Đầu ra: PNG, JPG, WEBP

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Higher scale = more AI processing time. 4x may take up to 30 seconds.

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An toàn & Bảo mật
Xóa file sau 2 giờ
Xử lý nhanh
Không cần tài khoản
Cực Nhanh

How to Convert

Chuyển đổi bất kỳ file nào trong vài giây — không cần phần mềm, không cần đăng ký.

01
Tải lên

Tải lên file âm thanh

02
Chọn định dạng

Chọn định dạng đầu ra

03
Tải xuống

Nhận file đã chuyển đổi

Tại sao EasyConv

Why Use EasyConv

Professional-grade conversion with features designed for real-world workflows.

Kiểm soát chất lượng

Điều chỉnh cài đặt chất lượng.

4x Detail Enhancement

A 500×500 image becomes a crisp 2000×2000 at 4x — suitable for large prints and high-DPI displays.

Photos & Illustrations

Works on photographs, anime artwork, digital illustrations, and screenshots — separate models optimise each type.

Xử lý an toàn

File được xử lý an toàn và bảo mật.

Colour Fidelity

The upscaler preserves and enhances original colours — no colour shifting or desaturation artefacts.

Tất cả định dạng chính

Hỗ trợ tất cả các định dạng phổ biến.

300+ Định dạng

Supported Formats

Detailed breakdown of every format supported by this converter.

Format Description Extension Use Case
JPG INPUT Upscale JPEG photos .jpg Portrait photos, landscapes, product images
PNG INPUT Upscale PNG with transparency .png UI screenshots, logos, illustrations
WEBP INPUT Upscale modern WebP images .webp Web images, downloaded assets
PNG OUTPUT (2X) Double original resolution .png Retina displays, web 2x assets
PNG OUTPUT (3X) Triple original resolution .png Large prints, HD mockups
PNG OUTPUT (4X) Quadruple original resolution .png Poster prints, canvas art, restoration
3 Bước Đơn giản

Frequently Asked Questions

Everything you need to know about this conversion tool.

We use Real-ESRGAN (Real-Enhanced Super-Resolution Generative Adversarial Network), a state-of-the-art model trained on real-world degraded images for natural-looking upscaling.

Significantly better. Standard bicubic enlargement just blurs pixels. Real-ESRGAN synthesises realistic textures, sharpens edges, and fills in plausible detail based on learned patterns.

Input images are limited to 2000×2000 pixels. At 4x scale this produces a 8000×8000 output (~64 megapixels), sufficient for A0-size prints at 96 dpi.

2x and 3x scale typically complete in 5–15 seconds. 4x upscaling on large images may take 20–30 seconds depending on server GPU load.

Yes. We use the Real-ESRGAN anime model for illustrated content, which preserves clean line art and flat colours better than the standard photo model.

AI upscaling can recover sharpness from mild blur. Severely blurry or low-resolution images (below 100px) will see improvement but cannot recover detail that was never captured.
12M+ người dùng tin tưởng

Who Uses This Tool

Real-world use cases from professionals across different industries.

Print Designer
Enlarge for Large-Format Print

Upscale a 500×500 web logo to 2000×2000 at 4x for crisp A4 or A3 print without the blurring that bicubic enlargement produces.

Content Restorer
Restore Old or Low-Res Photos

Bring new life to scanned prints, old family photos, or low-resolution archive images by upscaling with AI-generated detail enhancement.

Game thủ
Upscale Pixel Art for HiDPI

Use the anime/illustration model to upscale pixel-art game sprites 2x or 4x while preserving sharp edges and clean colour fills.

E-commerce Seller
Improve Low-Res Product Images

Upscale supplier product photos that arrived too small for your listing requirements to a minimum 1000×1000 without JPEG artefacts.

Digital Artist
Upscale Artwork for High-Res Sale

Enlarge digital illustrations from screen resolution (72 dpi) to print resolution (300 dpi) for art prints and Redbubble/Society6 listings.

Photographer
Recover Cropped-Down Images

If you over-cropped a photo and lost too many pixels, upscale 2x or 4x to recover enough resolution for your target use case.

Tại sao EasyConv

So sánh

Xem cách chúng tôi so sánh với các giải pháp khác

Feature Our Tool
EasyConv
Photoshop Topaz Gigapixel
Mô hình AI Real-ESRGAN Preserve Details 2.0
Hệ số 2x, 3x, 4x 2x only
Anime / illustration mode
Không làm mờ bicubic Partial
Tăng tốc GPU
Tự động xóa file (2h)
Miễn phí
API access Pro Paid
Technical Specifications

Technical Specifications

Detailed technical information about our conversion engine.

Limits
  • Max input: 2000 × 2000 px (free)
  • Max output at 4x: 8000 × 8000 px (~64 MP)
  • Supported inputs: JPG, PNG, WebP
Real-ESRGAN super-resolution AI upscaling ESRGAN GPU neural network
Engine
Real-ESRGAN v0.3 (photo) + Real-ESRGAN Anime6B (illustration)
Chất lượng
PNG output at full upscaled resolution; perceptual detail hallucination from trained model weights
Speed
2x: ~5–10 s; 3x: ~10–20 s; 4x: ~20–30 s depending on input size and GPU load
Security
HTTPS transfer · isolated GPU session · auto-purged in 2 h
Model
Real-ESRGAN (GAN-based SR)
Hardware
NVIDIA GPU inference
Output format
High-res PNG
Hướng dẫn đầy đủ

AI Image Upscaling Explained: Real-ESRGAN vs Traditional Enlargement

For decades, enlarging a digital image meant blurry, blocky results. AI super-resolution changed that. Modern models like Real-ESRGAN generate photorealistic detail rather than just interpolating pixels. Here is how it works and how to get the best results.

Why Traditional Upscaling Fails

Classical upscaling algorithms — bicubic, bilinear, Lanczos — work by interpolating values between existing pixels. They have no knowledge of what the image "should" look like at higher resolution, so they produce smooth but blurry results. Edge sharpness is lost, fine textures become mushy, and text or line art develops halos. The larger the scale factor, the worse the result.

How Real-ESRGAN Generates Detail

Real-ESRGAN is a Generative Adversarial Network trained on millions of real-world high-resolution images alongside artificially degraded (downsampled, blurred, compressed) versions. The generator learns to map low-resolution input to high-resolution output that is statistically indistinguishable from genuine high-res photos. It does not merely interpolate — it hallucinates plausible detail based on learned patterns in textures, edges, and structures.

Photo Model vs Anime Model: Which to Use

The standard Real-ESRGAN model is optimised for photographs with natural textures (skin, grass, fabric, architecture). It adds grain and texture detail that matches photo characteristics. The Anime6B model is optimised for drawn content: flat colour regions stay flat, linework stays crisp, and the model avoids adding photographic noise to illustrated elements. Always choose the model that matches your content type for best results.

Maximum Input and Output Resolution Limits

AI upscaling is computationally expensive. Processing a 2000×2000 image at 4x produces an 8000×8000 pixel (64 megapixel) output — equivalent to a medium-format camera. We cap free inputs at 2000×2000 to keep processing times reasonable. If your input is larger, resize it to 2000px on the longest edge first using our Image Resizer, then upscale.

Practical Tips for Best AI Upscaling Results

For photographs: remove compression artefacts first by running through the Image Compressor at quality 95 to clean up JPEG blocking before upscaling. For game sprites: use 4x with the anime model and ensure your input is at the original pixel-art resolution (no prior bicubic scaling). For print output: upscale to at least 300 dpi for your intended print size — a 4-inch print needs 1200px minimum.

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