Image Restoration by a Mixed High-Order Total Variation and <svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" style="vertical-align:-4.199599pt" id="M1" height="16.4602pt" version="1.1" viewBox="-0.0657574 -12.2606 10.8635 16.4602" width="10.8635pt"><g transform="matrix(.017,0,0,-0.017,0,0)"><path id="g113-109" d="M238 681C243 705 239 712 230 712C217 712 156 682 75 674L70 648H105C148 648 153 641 144 598L39 110C18 11 35 -12 55 -12C90 -12 166 36 221 103L205 125C174 93 130 65 118 65C112 65 108 68 114 96L238 681Z"/></g><g transform="matrix(.012,0,0,-0.012,4.187,4.134)"><path id="g50-50" d="M389 0V32C297 38 291 46 291 118V635C234 613 175 595 109 583V556L161 554C203 552 207 547 207 497V118C207 46 201 38 110 32V0H389Z"/></g></svg> Regularization Model

<div>SNR versus iterations with four different methods.</div>

Mathematical Problems in Engineering

fig7

Figure 7

Figure 7: Image Restoration by a Mixed High-Order Total Variation and <svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" style="vertical-align:-4.199599pt" id="M1" height="16.4602pt" version="1.1" viewBox="-0.0657574 -12.2606 10.8635 16.4602" width="10.8635pt"><g transform="matrix(.017,0,0,-0.017,0,0)"><path id="g113-109" d="M238 681C243 705 239 712 230 712C217 712 156 682 75 674L70 648H105C148 648 153 641 144 598L39 110C18 11 35 -12 55 -12C90 -12 166 36 221 103L205 125C174 93 130 65 118 65C112 65 108 68 114 96L238 681Z"/></g><g transform="matrix(.012,0,0,-0.012,4.187,4.134)"><path id="g50-50" d="M389 0V32C297 38 291 46 291 118V635C234 613 175 595 109 583V556L161 554C203 552 207 547 207 497V118C207 46 201 38 110 32V0H389Z"/></g></svg> Regularization Model 

Mathematical Problems in Engineering

Image Restoration by a Mixed High-Order Total Variation and Regularization Model

Figure 7