page_title: Inpainting
section_title: Digital Inpainting
hierarchical_section_title: Inpainting / Methods / Digital Inpainting
caption_attribution_description: Example of digital restorations and reconstruction of antique image "Doi călușari"
context_page_description: Inpainting is a conservation process where damaged, deteriorating, or missing parts of an artwork are filled in to present a complete image. This process can be applied to both physical and digital art mediums such as oil or acrylic paintings, chemical photographic prints, 3-dimensional sculptures, or digital images and video.
  With its roots in physical artwork, such as painting and sculpture, traditional inpainting is performed by a trained art conservator who has carefully studied the artwork to determine the mediums and techniques used in the piece, potential risks of treatments, and ethical appropriateness of treatment.
context_section_description: There are currently many programs in use that are able to reconstruct missing or damaged areas of digital photographs and videos. Most widely known for use with digital images is Adobe Photoshop. Since the digital files are able to be duplicated, any restorative alterations should be made to the duplicate file, while maintaining the original files in an archive. Given the various abilities of the digital camera and the digitization of old photos, inpainting has become an automatic process that can be performed on digital images. More than mere scratch removal, the inpainting techniques can also be applied to object removal, text removal, and other automatic modifications of images and videos. Furthermore, they can also be observed in applications like image compression and super resolution.
  In photography and cinema, it is used for film restoration to reverse, repair, or mitigate deterioration (e.g. physical damage such as cracks in photographs or scratches and dust spots in film or chemical damage resulting in image loss; see infrared cleaning). It can also be used for removing red-eye, the stamped date from photographs, and removing objects for creative effect. 
  This technique can be used to replace any lost blocks in the coding and transmission of images, for example, in a streaming video. It can also be used to remove logos in videos.
  Deep learning neural network based inpainting can be used for decensoring images.
  Three main groups of 2D image inpainting algorithms can be found in literature. The first one to be noted is structural (or geometric) inpainting, the second one is texture inpainting, and the last one is a combination of these two techniques. All these inpainting methods have one thing in common: they use the information of the known or non-destroyed image areas in order to fill the gap, similar to how physical images are restored.
caption: Digital Image Restoration and Reconstraction
exif: {"Image ImageWidth": "2000", "Image ImageLength": "1200", "Image BitsPerSample": "[8, 8, 8, 8]", "Image PhotometricInterpretation": "1", "Image Orientation": "Horizontal (normal)", "Image SamplesPerPixel": "4", "Image XResolution": "300", "Image YResolution": "300", "Image ResolutionUnit": "Pixels/Inch", "Image Software": "Adobe Photoshop CS5 Macintosh", "Image DateTime": "2014:01:20 14:56:48", "Image ExifOffset": "232", "Thumbnail Compression": "JPEG (old-style)", "Thumbnail XResolution": "72", "Thumbnail YResolution": "72", "Thumbnail ResolutionUnit": "Pixels/Inch", "Thumbnail JPEGInterchangeFormat": "382", "Thumbnail JPEGInterchangeFormatLength": "7054", "EXIF ExifVersion": "0221", "EXIF ColorSpace": "Uncalibrated", "EXIF ExifImageWidth": "926", "EXIF ExifImageLength": "600"}