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Why Image Compression Is a Multi-Constraint Engineering Problem, Not Just a Size Target

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Compressing an image to a specific file size involves satisfying multiple simultaneous constraints — file format, dimensions, byte count, and visual quality — not just one. Simply targeting a quality setting or a rounded label like '100 KB' is unreliable, since encoders do not reduce file size proportionally and byte definitions can vary between systems. A practical approach involves iterating over candidate quality values, measuring actual output blob sizes, and retaining only results that genuinely satisfy the size bound. When dimension requirements are fixed, a tool should clearly report failure rather than deliver a falsely optimistic result; when resizing is permitted, that should be a separate, explicit user choice. Format conversions such as switching to JPEG or WebP also carry trade-offs like loss of transparency and must be surfaced to the user before download.

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