Bild-Wasserzeichen

A visible watermark deters casual theft and makes unauthorized use immediately attributable, but it does not prevent a determined person from removing it. The protection level depends entirely on how the watermark is applied. A semi-transparent text or logo overlay rendered onto the image using the Canvas 2D API — which is what this tool does — can potentially be cropped out, cloned out with generative fill tools, or masked if it does not cover enough of the image's key subject area. The most effective visible watermarking strategy is to place text diagonally across the focal point of the image at roughly 30–50% opacity, making removal require altering the most valuable part of the composition. For highest deterrence, use a repeated tiled pattern rather than a single corner mark, since tiled patterns are far harder to remove convincingly. Invisible steganographic watermarks — where data is embedded into pixel values imperceptibly — require specialized encoding libraries and are beyond the scope of this browser-based tool. Copyright law provides legal protection regardless of whether a watermark is present: registering your work with the relevant copyright authority gives you the strongest basis for enforcement action if infringement occurs. All watermarking runs entirely in your browser using the Canvas API — no data leaves your device, and your original images are never uploaded anywhere. As a practical tip, export the watermarked image as PNG to preserve maximum quality; JPEG recompression can subtly degrade watermark text sharpness, which matters if you need the attribution to remain legible at small display sizes.

Font size for a watermark has no universal answer because legibility depends on the resolution of the output image, the length of your watermark text, and the viewing size at which the image will typically be displayed. The tool renders text onto a Canvas element at the image's native pixel dimensions, so the font size value maps directly to CSS pixels at the original resolution. As a working rule, for a typical 2000-pixel-wide photograph, a font size between 60 and 100 pixels produces text that is clearly readable in the full-resolution file, scales down reasonably in web thumbnails, and is difficult to crop out if centered. For lower-resolution images in the 800–1200 pixel range, font sizes between 30 and 60 pixels are generally appropriate. Very short watermarks like a website URL or a name stay legible at smaller sizes; longer copyright statements including the symbol, year, and full name need larger sizes or a multi-line layout to remain readable. Contrast matters more than size alone: a large font in a color close to the background tone will be less visible than a smaller font with strong contrast or a drop-shadow applied. Opacity between 40% and 70% usually balances visibility with not overwhelming the image content. All rendering happens entirely in your browser — no data leaves your device. As a practical tip, use the live preview canvas before exporting to test how the size reads at the intended display dimensions; zoom out your browser window to simulate how the watermark will look on smaller screens.

The difference comes from how JPEG and PNG encode image data at a fundamental level. JPEG uses lossy compression based on the Discrete Cosine Transform (DCT), which divides the image into 8×8 pixel blocks and discards high-frequency detail to reduce file size. Anti-aliased text and smooth gradient overlays — exactly what a font-rendered watermark consists of — contain high-frequency transitions between letterform edges and background pixels. DCT compression blurs and introduces block-shaped ringing artifacts around those transitions, which makes fine text appear jagged, blurry, or grainy depending on the JPEG quality setting used at export. PNG uses lossless DEFLATE compression, which stores every pixel value exactly as the Canvas renders it, so smooth anti-aliased edges are preserved perfectly. If your watermarked output must be JPEG — for example, to keep file size small for web publishing — use a quality setting of 90 or higher during export to substantially reduce DCT artifacts around the text. Some degradation will still occur at any JPEG quality below 100, particularly on sub-pixel-smooth text edges. The Canvas 2D API renders text with full sub-pixel anti-aliasing at the source, meaning the information is there but JPEG encoding discards part of it. All processing runs entirely in your browser — no data leaves your device. As a practical tip, always keep a PNG master of the watermarked image and create JPEG derivatives from that when file size matters, rather than re-watermarking a JPEG original.

The current version of the watermark tool is designed for single-image processing — you select one image, configure placement, text, and opacity, then export. It does not include a built-in batch queue. However, if you need to process many images, the tool's architecture is entirely browser-side using the Canvas 2D API, which means no server bottleneck exists in principle; the limitation is the tool's UI, not the underlying technology. For true batch watermarking of hundreds of files, the most practical approaches outside this tool are: using a desktop application like IrfanView, XnConvert, or GIMP's Script-Fu batch mode on Windows or macOS; using FFmpeg with the drawtext or overlay filter in a shell script if you are comfortable with the command line; or using ImageMagick's mogrify command with the -annotate option to apply consistent text across an entire directory in a single command. If your images are already hosted somewhere, a serverless function using the Canvas API on Node.js or the Sharp library can apply watermarks programmatically at scale. The WikiPlus watermark tool is best suited for individual images where you want fine-grained visual control over placement and appearance without installing any software. All processing runs entirely in your browser — no data leaves your device. As a practical tip, before doing a large batch run with any tool, test your watermark configuration on two or three representative images first to confirm the font size, opacity, and positioning look correct at the actual export resolution.