FIX BLURRY VIDEO

Motion blur occurs when objects or camera move during exposure, creating directional smear where moving elements streak across the frame. This is common in handheld video, action sports footage, and low-light scenes with slow shutter speeds. The image information exists but is distributed across multiple pixels. AI can analyze the directional characteristics and reconstruct sharper edges by intelligently redistributing this smeared data. Results are often dramatic because the detail is recoverable—it's just spread out.

Focus blur happens when the lens fails to converge light properly on the sensor, creating uniformly soft images where no part appears sharp. This occurs with auto-focus struggles in low light, low-contrast subjects, or incorrect manual focus setting. Unlike motion blur, focus blur means the detail information was never captured. AI cannot fully restore what was never recorded, but can enhance edge definition and apply intelligent sharpening to make footage appear significantly sharper and more defined.

Gaussian blur is the soft, uniform blur that results from low resolution, heavy compression, or poor capture quality. Unlike motion blur's directional smear or focus blur's optical failure, Gaussian blur simply lacks fine detail across the entire image. This is common with old cameras, budget devices, and heavily compressed social media video. AI upscaling combined with sharpening can generate convincing detail that wasn't present in the original, creating the perception of sharpness and clarity.

Video codecs discard high-frequency detail information to reduce file sizes, creating soft, muddy footage lacking crisp edges. This is especially visible with highly compressed social media video, screen recordings, and downloaded content. The blur isn't optical—it's lost detail from aggressive compression. AI can reconstruct plausible texture and edge information by learning what natural sharp video looks like, partially reversing compression damage and restoring apparent sharpness.